Computational Pathology

• Developing and validating diagnostic, prognostic and predictive computational biomarkers.

• Furthering disease knowledge with data-driven approaches.

• Understanding underlying factors that drive algorithmic decision.

• Bridging the knowledge gap between clinicians and computational scientists.

• Mentoring and inspiring the next generation of computational pathology researchers.

• Optimization of intuitive interfaces for digital pathology workflow.

• Operationalization of digital pathology IT workflow.

Journal Manuscripts

1. M.J.van den Bent, M.A.Vogelbaum, T.Cloughesy, N.Galldiks, N.L.Albert, J.-C.Tonn, E.Avila, J.Fangusaro, D.Mirsky, A.Sahgal, R.Soffietti, P.Karschnia, M.Mehta, M.M.Kim, F.Boele, J.T.Huse, L.Nayak, M.J.Lim-Fat, E.le Rhun, A.Desjardins, E.Q.Lee, U.Chukwueke, J.A.F.Koekkoek, T.Mendoza, A.R.Loughan, J.A.Budhu, S.Bakas, R.Y.Huang, J.E.Villanueva-Meyer, J.P.Leone, H.Okada, D.A.Reardon, W.L.Bi, P.Y.Wen, S.M.Chang, “Response Assessment in Neuro-Oncology (RANO) 2009-2025: Broad Scope and Implementation – A Progress Report”, Neuro-Oncology, 27(9):2209-2224, 2025
2. A.Linardos, S.Pati, B.Edwards, U.Baid, P.Foley, K.Ta, V.Chung, M.Sheller, M.I.Khan, M.Jafaritadi, E.Kontio, S.Khan, L.Mächler, I.Ezhov, S.Shit, J.C.Paetzold, G.Grimberg, M.A.Nickel, D.Naccache, V.Siomos, J.Passerat-Palmbach, G.Tarroni, D.Kim, L.L.Klausmann, P.Shah, B.Menze, D.Makris, S.Bakas, “The Federated Tumor Segmentation (FeTS) Challenge 2024: Efficient and Robust Aggregation Methods”, Machine Learning for Biomedical Imaging, 3:757-774, 2025
3. K.Noller, T.Botsis, P.G.Camara, L.Ciotti, L.A.D.Cooper, J.Goecks, M.Griffith, B.Haas, T.Ideker, R.Karchin, D.Kontos, J.Lai, D.S.Marcus, C.A.Meyer, K.M.Naegle, S.Pati, B.Peters, D.Pratt, B.J.Raphael, M.Reich, G.Savova, C.Wright, E.J.Fertig, S.Bakas, “Informatics at the Frontier of Cancer Research”, Cancer Research, 85(16):2967-2986, 2025
4. B.H.Kann, A.Vossough, SC.Brüningk, A.M.Familiar, M.Aboian, M.G.Linguraru, K.Yeom, S.M.Chang, D.Hargrave, D.Mirsky, P.B.Storm, R.Y.Huang, A.C.Resnick, M.Weller, S.Mueller, M.Prados, A.Peet, J.E.Villanueva-Meyer, S.Bakas, J.R.Fangusaro, A.Nabavizadeh, A.F.Kazerooni, for the Response Assessment in Pediatric Neuro Oncology (RAPNO) group, “Artificial Intelligence for Response Assessment in Pediatric Neuro Oncology (AI-RAPNO), part1: review of the current state of the art”, The Lancet Oncology, 26(11):e597-e606, 2025
5. A.F.Kazerooni, A.M.Familiar, M.Aboian, S.C.Brüningk, A.Vossough, M.G.Linguraru, R.Y.Huang, D.Hargrave, A.Peet, A.C.Resnick, P.B.Storm, D.Mirsky, K.Yeom, M.Weller, M.Prados, S.M.Chang, S.Mueller, J.E.Villanueva-Meyer, S.Bakas, J.R.Fangusaro, B.H.Kann, A.Nabavizadeh, for the Response Assessment in Pediatric Neuro Oncology (RAPNO) group, “Artificial Intelligence for Response Assessment in Pediatric Neuro Oncology (AI-RAPNO), part 2: Challenges, Opportunities, and Recommendations for Clinical Translation”, The Lancet Oncology, 26(11):e607-e618, 2025
6. A.Crimi, S.Bakas, “Spatiotemporal & AI Trends in Neuroscience, Neuroimaging, and Neurooncology”, Frontiers in Neuroimaging, 4:1716335, 2025
7. M.Zenk, U.Baid, S.Pati, A.Linardos, B.Edwards, M.Sheller, P.Foley, A.Aristizabal, D.Zimmerer, A.Gruzdev, J.Martin, R.Shinohara, A.Reinke, F.Isensee, S.Parampottupadam, K.Parekh, R.Floca, H.Kassem, B.Baheti, S.Thakur, V.Chung, K.Kushibar, K.Lekadir, M.Jiang, Y.Yin, H.Yang, Q.Liu, C.Chen, Q.Dou, P.-A..Heng, X.Zhang, S.Zhang, M.Khan, M.Azeem, M.Jafaritadi, E.Alhoniemi, E.Kontio, S.A..Khan, L.Machler, I.Ezhov, F.Kofler, S.Shit, J.C.Paetzold, T.Loehr, B.Wiestler, H.Peiris, K.Pawar, S.Zhong, Z.Chen, M.Hayat, G.Egan, M.Harandi, E.I.Polat, G.Polat, A.Kocyigit, A.Temizel, A.Tuladhar, L.Tyagi, R.Souza, N.Forkert, P.Mouches, M.Wilms, V.Shambhat, A.Maurya, S.S.Danannavar, R.Kalla, V.K.Anand, G.Krishnamurthi, S.Nalawade, C.Ganesh, B.Wagner, D.Reddy, Y.Das, F.F.Yu, B.Fei, A.J.Madhuranthakam, J.Maldjian, G.Singh, J.Ren, W.Zhang, N.An, Q.Hu, Y.Zhang, Y.Zhou, V.Siomos, A.Rawat, G.Zizzo, S.Kadhe, J.P.Epperlein, S.Braghin, Y.Wang, R.Kanagavelu, Q.Wei, Y.Yang, Y.Liu, K.Kotowski, S.Adamski, B.Machura, W.Malara, L.Zarudzki, J.Nalepa, Y.Shi, H.Gao, S.Avestimehr, Y.Yan, A.S.Akbar, E.Kondrateva, H.Yang, Z.Li, H.-Y.Wu, J.Roth, C.Saueressig, A.Milesi, Q.D.Nguyen, N.J.Gruenhagen, T.-M.Huang, J.Ma, H.S.H.Singh, N.-Y.Pan, D.Zhang, R.A.Zeineldin, M.Futrega, Y.Yuan, G.M.Conte, X.Feng, Q.D.Pham, Y.Xia, Z.Jiang, H.M.Luu, M.Dobko, A.Carre, B.Tuchinov, H.Mohy-ud-Din, S.Alam, A.Singh, N.Shah, W.Wang, C.Sako, M.Bilello, S.Ghodasara, S.Mohan, C.Davatzikos, E.Calabrese, J.Rudie, J.Villanueva-Meyer, S.Cha, C.Hess, J.Mongan, M.Ingalhalikar, M.Jadhav, U.Pandey, J.Saini, R.Y.Huang, K.Chang, M.-S.To, S.Bhardwaj, C.Chong, M.Agzarian, M.Kozubek, F.Lux, J.Michalek, P.Matula, M.Kevrkovsky, T.Kopvrivova, M.Dostal, V.Vybihal, M.C.Pinho, J.Holcomb, M.Metz, R.Jain, M.Lee, Y.W.Lui, P.Tiwari, R.Verma, R.Bareja, I.Yadav, J.Chen, N.Kumar, Y.Gusev, K.Bhuvaneshwar, A.Sayah, C.Bencheqroun, A.Belouali, S.Madhavan, R.Colen, A.Kotrotsou, P.Vollmuth, G.Brugnara, C.J.Preetha, F.Sahm, M.Bendszus, W.Wick, A.Mahajan, C.Balano-Quintero, J.Capellades, J.Puig, Y.S.Choi, S.-K.Lee, J.H.Chang, S.S.Ahn, H.F.Shaykh, A.Herrera-Trujillo, M.Trujillo, W.Escobar, A.Abello, J.Bernal, J.Gomez, P.LaMontagne, D.Marcus, M.Milchenko, A.Nazeri, B.Landman, K.Ramadass, K.Xu, S.Chotai, L.B.Chambless, A.Mistry, R.C.Thompson, A.Srinivasan, J.R.Bapuraj, A.Rao, N.Wang, O.Yoshiaki, T.Moritani, S.Turk, J.Lee, S.Prabhudesai, J.Garrett, M.Larson, R.Jeraj, H.Li, T.Weiss, M.Weller, A.Bink, B.Pouymayou, S.Sharma, T.-C.Tseng, S.Adabi, A.X.Falcao, S.B.Martins, B.C.A.Teixeira, F.Sprenger, D.Menotti, D.R.Lucio, S.P.Niclou, O.Keunen, A.-C.Hau, E.Pelaez, H.Franco-Maldonado, F.Loayza, S.Quevedo, R.McKinley, J.Slotboom, P.Radojewski, R.Meier, R.Wiest, J.Trenkler, J.Pichler, G.Necker, A.Haunschmidt, S.Meckel, P.Guevara, E.Torche, C.Mendoza, F.Vera, E.Rios, E.Lopez, S.A.Velastin, J.Choi, S.Baek, Y.Kim, H.Ismael, B.Allen, J.M.Buatti, P.Zampakis, V.Panagiotopoulos, P.Tsiganos, S.Alexiou, I.Haliassos, E.I.Zacharaki, K.Moustakas, C.Kalogeropoulou, D.M.Kardamakis, B.Luo, L.Poisson, N.Wen, M.Vallieres, M.A.L.Loutfi, D.Fortin, M.Lepage, F.Moron, J.Mandel, G.Shukla, S.Liem, G.S.Alexandre, J.Lombardo, J.D.Palmer, A.E.Flanders, A.P.Dicker, G.Ogbole, D.Oyekunle, O.Odafe-Oyibotha, B.Osobu, M.S.ikima, M.Soneye, F.Dako, A.Dorcas, D.Murcia, E.Fu, R.Haas, J.Thompson, D.R.Ormond, S.Currie, K.Fatania, R.Frood, A.L.Simpson, J.J.Peoples, R.Hu, D.Cutler, F.Y.Moraes, A.Tran, M.Hamghalam, M.A.Boss, J.Gimpel, D.Kattil Veettil, K.Schmidt, L.Cimino, C.Price, B.Bialecki, S.Marella, C.Apgar, A.Jakab, M.-A.Weber, E.Colak, J.Kleesiek, J.B.Freymann, J.S.Kirby, L.Maier-Hein, J.Albrecht, P.Mattson, A.Karargyris, P.Shah, B.Menze, K.Maier-Hein, S.Bakas, “Towards Fair Decentralized Benchmarking of Healthcare AI Algorithms with the Federated Tumor Segmentation (FeTS) Challenge”, Nature Communications, 16:6274, 2025
8. S.Innani, W.R.Bell, M.P.Nasrallah ,B.Baheti, S.Bakas, AI-driven WHO 2021 classification of gliomas based only on H&E-stained slides, Neuro-Oncology, 28(1):282-296, 2025
9. J.Zhong, Y.Xing, Y.Hu, D.Ding, X.Liu, S.Dai, J.Lu, J.Yang, J.Chu, Y.Song, M.Lu, H.Zhang, G.Yang, W.Yao, B.Kocak, B.Baessler, S.Bakas, R.Cuocolo, L.Maier-Hein, N.Mercaldo, H.Müller, F.Orlhac, D.P.Dos Santos, A.Stanzione, L.Ugga, A.Zwanenburg, “Interpretation of CheckList for EvaluAtion of Radiomics research (CLEAR)”, Chinese Journal of Evidence-Based Medicine, 25:932-942, 2025
10. B.Baheti, S.Rai, S.Innani, G.Mehdiratta, W.R.Bell, S.C.Guntuku, M.P.Nasrallah, S.Bakas, “Multimodal Explainable AI for Prognostic Stratification of Glioblastoma Patients”, Modern Pathology, 38(9):100797, 2025
11. S.Pati, S.Wagner, S.Thakur, E.Calabrese, R.T.Shinohara, S.Bakas, “An Unsupervised Brain Extraction Quality Control Approach for Efficient Neuro-Oncology Studies”, Journal of Imaging Informatics in Medicine, Online ahead of print, 2025.
12. S.Thakur, S.Pati, J.Wu, R.Panchumarthy, D.Karkada, A.Kozlov, V.Shamporov, A.Suslov, D.Lyakhov, M.Proshin, P.Shah, D.Makris, S.Bakas, “Optimization of Deep Learning Models for Inference in Low Resource Environments”, Computers in Biology and Medicine, 196:110615, 2025
13. S.Innani, W.R.Bell, H.Harmsen, M.P.Nasrallah, B.Baheti , S.Bakas, “Interpretable artificial intelligence-based determination of glioma IDH mutation status directly from histology slides”, NeuroOncology Advances, 7(1):vdaf140, 2025
14. A.F.Kazerooni, N.Khalili, X.Liu, D.Haldar, Z.Jiang, A.Zapaishchykova, J.Pavaine, L.M.Shah, B.V.Jones, N.Sheth, S.P.Prabhu, A.S.McAllister, W.Tu, K.K.Nandolia, A.F.Rodriguez, I.S.Shaikh, M.Sanchez-Montano, H.A.Lai, M.Adewole, J.Albrecht, U.Anazodo, H.Anderson, S.M.Anwar, A.Aristizabal, S.Bagheri, U.Baid, T.Bergquist, A.J.Borja, E.Calabrese, V.Chung, G.-M.Conte, J.Eddy, I.Ezhov, A.M.Familiar, K.Farahani, D.Gandhi, A.Gottipati, S.Haldar, J.E.Iglesias, A.Janas, E.Elaine, A.Karargyris, H.Kassem, F.Kofler, D.LaBella, K.V.Leemput, H.B.Li, N.Maleki, Z.Meier, B.Menze, A.W.Moawad, S.Pati, M.Piraud, T.Poussaint, Z.J.Reitman, J.D.Rudie, R.Saluja, M.Sheller, R.T.Shinohara, K.Viswanathan, C.Wang, B.Wiestler, W.F.Wiggins, C.Davatzikos, P.B.Storm, M.Bornhorst, R.Packer, T.Hummel, P.deBlank, L.Hoffman, M.Aboian, A.Nabavizadeh, J.B.Ware, B.H.Kann, B.Rood, A.Resnick, S.Bakas, A.Vossough, M.G.Linguraru, “BraTS-PEDs: Results of the Multi-Consortium International Pediatric Brain Tumor Segmentation Challenge 2023”, Machine Learning for Biomedical Imaging, 3, 2025
15. H.Akbari*, S.Bakas*, S.Chiharu*, A.F.Kazerooni, J.Villanueva-Meyer, E.Mamourian, F.Liu, Q.Cao, R.T.Shinohara, U.Baid, A.Getka, S.Pati, A.Singh, E.Calabrese, S.Chang, J.Rudie, A.Sotiras, P.LaMontagne, D.S.Marcus, M.Milchenko, A.Nazeri, C.Balana, J.Capellades, J.Puig, C.Badve, J.S.Barnholtz-Sloan, A.E.Sloan, V.Vadmal, K.Waite, M.Ak, R.R.Colen, Y.W.Park, S.S.Ahn, J.H.Chang, Y.S.Choi, S.-K.Lee, G.S.Alexander, A.S.Ali, A.P.Dicker, A.E.Flanders, S.Liem, J.Lombardo, W.Shi, G.Shukla, B.Griffith, L.M.Poisson, L.R.Rogers, A.Kotrotsou, T.C.Booth, R.Jain, M.Lee, A.Mahajan, A.Chakravarti, J.D.Palmer, D.DiConstanzo, H.Fathallah-Shaykh, S.Cepeda, O.G.Santonocito, A.L.D.Stefano, B.Wiestler, E.R.Melhem, G.F.Woodworth, P.Tiwari, P.Valdes, Y.Matsumoto, Y.Otani, R.Imoto, M.Aboian, S.Koizumi, K.Kurozumi, T.Kawakatsu, K.Alexander, L.Satgunaseelan, A.M.Rulseh, S.J.Bagley, M.Bilello, Z.Binder, S.Brem, A.S.Desai, R.A.Lustig, E.Maloney, T.Prior, N.Amankulor, M.P.Nasrallah, D.M.O’Rourke, S.Mohan, C.Davatzikos, for the ReSPOND Consortium, “Machine Learning-based Prognostic Subgrouping of Glioblastoma: A Multi-center Study”, Neuro-Oncology, 27(4):1102-1115, 2025
16. M.Adewole, J.D.Rudie, A.Gbdamosi, O.Toyobo, C.Raymond, D.Zhang, O.Omidiji, R.Akinola, M.A.Suwaid, A.Emegoakor, N.Ojo, K.Aguh, C.Kalaiwo, G.Babatunde, A.Ogunleye, Y.Gbadamosi, K.Iorpagher, E.Calabrese, M.Aboian, M.Linguraru, J.Albrecht, B.Wiestler, F.Kofler, A.Janas, D.LaBella, A.F.Kzerooni, H.B.Li, J.E.Iglesias, K.Farahani, J.Eddy, T.Bergquist, V.Chung, R.T.Shinohara, W.Wiggins, Z.Reitman, C.Wang, X.Liu, Z.Jiang, A.Familiar, K.V.Leemput, C.Bukas, M.Piraud, G.Conte, E.Johansson, Z.Meier, B.H.Menze, U.Baid, S.Bakas, F.Dako, U.C.Anazodo, “The BraTS-Africa Dataset: Expanding the Brain Tumor Segmentation (BraTS) data to Capture African Populations”, Radiology: Artificial Intelligence, 7(4), 2025
17. D.LaBella, U.Baid, O.Khanna, S.McBurney-Lin, R.McLean, P.Nedelec, A.Rashid, N.H.Tahon, T.Altes, R.Bhalerao, Y.Dhemesh, D.Godfrey, F.Hilal, S.Floyd, A.Janas, A.F.Kazerooni, J.Kirkpatrick, C.Kent, F.Kofler, K.Leu, N.Maleki, B.Menze, M.Pajot, Z.J.Reitman, J.D.Rudie, R.Saluja, Y.Velichko, C.Wang, P.Warman, M.Adewole, J.Albrecht, U.Anazodo, S.M.Anwar, T.Bergquist, S.F.Chen, V.Chung, G.Conte, F.Dako, J.Eddy, I.Ezhov, A.Familiar, J.E.Iglesias, Z.Jiang, E.Johanson, K.V.Leemput, H.B.Li, M.G.Linguraru, X.Liu, A.Mahtabfar, Z.Meier, A.W.Moawad, J.Mongan, M.Piraud, R.T.Shinohara, W.F.Wiggins, A.H.Abayazeed, R.Akinola, A.Jakab, M.Bilello, M.Correia de Verdier, P.Crivellaro, C.Davatzikos, K.Farahani, J.Freymann, C.Hess, R.Huang, P.Lohmann, M.Moassefi, M.W.Pease, P.Vollmuth, N.Sollmann, D.Diffley, K.K.Nandolia, D.I.Warren, A.Hussain, P.Fehringer, Y.Bronstein, L.Deptula, E.G.Stein, M.Taherzadeh, E.Portela de Oliveira, A.Haughey, M.Kontzialis, L.Saba, B.Turner, M.M.Brüßeler, S.Ansari, A.Gkampenis, D.M.Weiss, A.Mansour, I.H.Shawali, N.Yordanov, J.M.Stein, R.Hourani, M.Y.Moshebah, A.M.Abouelatta, T.Rizvi, K.Willms, D.C.Martin, A.Okar, G.D’Anna, A.Taha, Y.Sharifi, S.Faghani, D.Kite, M.Pinho, M.A.Haider, A.Aristizabal, A.Karargyris, H.Kassem, S.Pati, M.Sheller, M.Alonso-Basanta, J.Villanueva-Meyer, A.M.Rauschecker, A.Nada, M.Aboian, A.E.Flanders, B.Wiestler, S.Bakas, E.Calabrese, “Analysis of the BraTS 2023 Intracranial Meningioma Segmentation Challenge”, Machine Learning for Biomedical Imaging, 3:38-58, 2025
18. M.H.Goreish, N,Gennaro, L.Perronne, G.Durak, A.A.Borhani, H,Savas, L.Kelahan, R.Avery, K.Subedi, T.A.Trabzonlu, U.Bagci, B.Turkbey, S.Bakas, S.Sachdev, R.Sumagin, B.A.Alexiev, P.H.de Viveiros, S.M.Pollack, Y.S.Velichko, “Paradoxical Response to Neoadjuvant Therapy in Undifferentiated Pleomorphic Sarcoma: Increased Tumor Size on MRI Associated with Favorable Pathology”, Cancers, 17(5):830, 2025
19. A.F.Kazerooni, H.Akbari, X.Hu, V.Bommineni, D.Grigoriadis, E.Toorens, C.Sako, E.Mamourian, D.Ballinger, R.Sussman, A.Singh, I.I.Verginadis, N.Dahmane, C.Koumenis, Z.A.Binder, S.Bagley, S.Mohan, A.Hatzigeorgiou, D.M.O’Rourke, T.Ganguly, S.De, S.Bakas, M.P.Nasrallah, C.Davatzikos, “The Radiogenomic and Spatiogenomic Landscapes of Glioblastoma and Their Relationship to Oncogenic Drivers”, Nature Communications Medicine, 5(55), 2025
20. K.Collins, S.Innani, K.Ebare, M.Saad, S.Siegmund, S.Williamson, F.Maclean, A.Matoso, A.Sangoi, M.Hirsch, D.D.Gondim, A.Acosta, B.Baheti, S.Bakas*, M.Idrees*, “Artificial Intelligence-Based Classification of Renal Oncocytic Neoplasms: Advancing From a 2-Class Model of Renal Oncocytoma and Low-Grade Oncocytic Tumor to a 3-Class Model Including Chromophobe Renal Cell Carcinoma”, Archives of Pathology & Laboratory Medicine, 149(10):922-929, 2025
21. Z. Zhang, Q. Yang, R. Shiradkar, T. Mirtti, S. Azamat, K. Xuan, J. Xu, A. Madabhushi, “A deep learning derived prostate zonal volume‐based biomarker from T2‐weighted MRI to distinguish between prostate cancer and benign prostatic hyperplasia”, Medical Physics, 52(8):e18053, 2025
22. A. Guha, V. Shah, T. Nahle, S. Singh, HH. Kunhiraman, F. Shehnaz, P. Nain, OM. Makram, M. Mahmoudi, S. Al-Kindi, A. Madabhushi, R. Shiradkar, H. Daoud, “Artificial Intelligence Applications in Cardio-Oncology: A Comprehensive Review”, Curr Cardiol Rep, 27(1):56, 2025
23. MA. Bilen, BT. Vo, Y. Liu, R. Greenwald, AH. Davarpanah, D. McGuire, R. Shiradkar, L. Li, A. Midya, B. Nazha, JT. Brown, S. Williams, W. Session, G. Russler, S. Caulfield, SS. Joshi, VM. Narayan, CP. Filson, K. Ogan, O. Kucuk, BC. Carthon, L. Del Balzo, A. Cohen, A. Boyanton, N. Prokhnevska, MA. Cardenas, E. Sobierajska, CS. Jansen, DH. Patil, E. Nicaise, AO. Osunkoya, HT. Kissick, VA. Master, “Neoadjuvant cabozantinib for locally advanced nonmetastatic clear cell renal cell carcinoma: a phase 2 trial”, Nature Cancer, 6(3):432–444, 2025
24. A. Midya, S. Tirumani, LK. Bittencourt, S. Azamat, S. Balakrishnan, A. Hiremath, S. Wido, P. Fu, L. Ponsky, A. Madabhushi, R. Shiradkar, “Population-Specific Radiomics From Biparametric Magnetic Resonance Imaging Improves Prostate Cancer Risk Stratification in African American Men”, JU Open Plus, 3(7):e00068, 2025

Peer Reviewed Full-length Conference Articles

1. S.Bakas, S.Thakur, U.Baid, A.Linardos, S.Pati, J.Doshi, R.T.Shinohara, “My Model Is Better Than Yours! Statistically-aware Ranking for Fair Benchmarking of AI Models”, Springer - MICCAI Segmentation, Classification, and Synthesis for Brain Tumors and Traumatic Brain Injuries - LNCS, 2025.
2. E.Deutscher, N.J.Tustison, A.Onicas, E.A.Wilde, M.Pease, S.Bakas, E.L.Dennis, “Automated Identification of Moderate-to-Severe Traumatic Brain Injury Lesions (AIMS-TBI) 2025 MICCAI Challenge”, Springer - MICCAI Segmentation, Classification, and Synthesis for Brain Tumors and Traumatic Brain Injuries - LNCS, 2025.
3. S. Anuyah, MM. Kaushik, SRKR. Dwarampudi, R. Shiradkar, A. Durresi, S. Chakraborty, “Automated knowledge graph construction using large language models and sentence complexity modelling”, Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, p. 15526–15550, 2025

Abstracts

1. C.Pitarch-Abaigar, S.Adap, H.Akbari, A.Flinn, N.J.Shah, K.-J.Langen, N.Galldiks, M.Pease, N.T.Gatson, P.S.LaViolette, C.Davatzikos, J.Parker, P.Lohmann, S.Bakas, “Glioblastoma beyond the enhancing tumor margins: a longitudinal case study comparing FET PET with MRI-based AI infiltration maps”, Neuro-Oncology, 27(Suppl_5):v43-v43, 2025
2. C.Pitarch-Abaigar, A.S.Hashemi, S.Adap, M.Pease, N.T.Gatson, J.Parker, B.Griffith, I.Lee, T.Walbert, J.Snyder, H.Noushmehr, S.Bakas, “Imaging Surrogate Signature of the Glioma Epigenetic Liquid Biopsy (GeLB) Score for Non-invasive Detection of Tumor Progression”, Neuro-Oncology, 27(Suppl_5):v43-v43, 2025
3. S. Innani, W.R.Bell, M.P.Nasrallah, B.Baheti, S.Bakas, “AI-based WHO 2021 classification of adult-type diffuse glioma solely from H&E-stained slides”, Neuro-Oncology, 27(Suppl_5):v256-v256, 2025
4. S. Innani, C.Pitarch-Abaigar, M.M.Majeed, H.Harmsen, W.R.Bell, D.Makris, S.Bakas, “AI-based prognostic risk stratification of adult-type diffuse gliomas using H&E-stained slides”, Neuro-Oncology, 27(Suppl_5):v257-v257, 2025
5. A.Winiarz, J.Hilgers, S.A.Bobholz, A.K.Lowman, S.R.Duenweg, B.Nath, B.Chao, F.Kyereme, J.Connelly, E.K.Mrachek, M.Krucoff, S.Bakas, N.Galldiks, P.S.LaViolette, P.Lohmann, “Association of FET PET tumor volume and radio-pathomic maps of cell density in newly diagnosed glioblastoma patients”, Neuro-Oncology, 27(Suppl_5):v297-v297, 2025
6. D.LaBella, H.Kassem, B.Edwards, M.Sheller, S.Pati, A.Aristizabal, R.Huang, U.Baid, A.Karargyris, S.Bakas, E.Calabrese, “FeTS 2.0: Federated learning sets benchmark in post-op GBM segmentation”, Neuro-Oncology, 27(Suppl_5):v289-v289, 2025
7. F.Yu, J.Guo, Y.Tian, J.A.Garcia, H.Akbari, Y.Matsumoto, R.Xing, T.Han, A.F.Kazerooni, S.Bakas, U.Baid, J.Villanueva-Meyer, S.Brem, R.A.Lustig, D.M.O'Rourke, S.Bagley, E.Calabrese, J.Rudie, S.Chang, P.LaMontagne, D.S.Marcus, C.Balana, J.Capellades, J.Puig, J.Barnholtz-Sloan, C.Badve, A.Sloan, K.Waite, R.Colen, Y.S.Choi, S.S.Ahn, A.P.Dicker, A.E.Flanders, W.Shi, B.Griffith, L.M.Poisson, T.C.Booth, R.Jain, A.Chakravarti, J.Palmer, S.Cepeda, B.Wiestler, E.R.Melhem, G.F.Woodworth, P.Tiwari, M.Aboian, S.Mohan, P.Chaudhari, M.Nasrallah, C.Davatzikos, “Self-supervised multimodal learning for survival prediction in glioblastoma: a multicenter study from the ReSPOND consortium”, Neuro-Oncology, 27(Suppl_5):v288-v288, 2025
8. S.P.Thakur, S.Malec, C.Pitarch-Abaigar, A.Linardos, S.Innani, S.Adap, U.Baid, S.Faghani, M.Moassefi, M.P.Nasrallah, J.T.Ahrendsen, V.Barresi, M.A.Gubbiotti, G.Y.Lopez, C.-H.G.Lucas, V.Chung, A.Karargyris, H.Kassem, M.L.Miller, S.Pati, B.Baheti, M.Wodzinski, H.Müller, J.Zhang, Y.Weng, K.Chen, R.Kumar, Vinit, M.Arora, T.Dhingra, S.R.Zahra, A.Gupta, A.A.Sandino, O.Krebs, J.Helgager, D.S.Becerra, N.J.Sandino, E.Romero, P.Tiwari, L.A.D.Cooper, J.T.Huse, W.R.Bell, S.Bakas, “BraTS-Pathology 2024: Insights and Future Directions Informed by the AI-RANO & RANO-RGP Effort to Assess Glioblastoma Heterogeneity”, Neuro-Oncology, 27(Suppl_5):v303-v304, 2025
9. J.Guo, F.Yu, Y.Matsumoto, J.A.Garcia, R.Xing, H.Akbari, U.Baid, S.Bakas, J.Barnholtz-Sloan, C.Balana, J.Puig, T.Booth, C.Badve, A.Sloan, B.Griffith, L.Poisson, A.P.Dicker, A.Flanders, W.Shi, R.Jain, J.Palmer, A.Mahajan, S.Cepeda, B.Wiestler, Y.W.Park, S.S.Ahn, J.H.Chang, M.Ak, R.Colen, J.Villanueva-Meyer, S.Chang, P.LaMontagne, D.Marcus, G.F.Woodworth, D.Parker, R.Verma, S.Brem, D.O'Rourke, S.Bagley, S.Mohan, M.P.Nasrallah, C.Davatzikos, on behalf of the ReSPOND consortium, “Unveiling glioblastoma heterogeneity with deep learning derived MRI subtyping: insights from the global ReSPOND consortium”, Neuro-Oncology, 27(Suppl_5):v280-v280, 2025
10. J.S.Park, J.Ha, S.P.Thakur, S.Bakas, E.Garyfallidis, “Multimodal, Multispecies and Pathology Invariant Skullstripping”, ISMRM, 2025
11. S. Thakur, U. Baid, A. M. Acosta, M. T Idrees, M. Feldman, S.Bakas, “AI-based robust testicular cancer triaging, a promise for an efficient and cost-effective diagnostic/predictive modality”, Cancer Research, 85 (8_Supplement_1): 2455, 2025
12. C. Moreno, R. Shiradkar, T. Pathak, K. Hammouda, I. Lawal, O. Abiodun-Ojo, MG. Sanda, D. Schuster, A. Osunkoya, “863 Visium-HD Spatial RNAseq Analysis of Aggressive Prostatic Adenocarcinoma (PCa) Identifies Distinct RNA Signatures That Distinguish Between Gleason Grade 4 and 5 Tumors, and Subset Associated with Stroma Adjacent to Pca”, Laboratory Investigation, 105(3), 2025
13. R. Shiradkar, T. Pathak, C. Winham, IO. Lawal, OA. Abiodun-Ojo, MG. Sanda, DM. Schuster, AO. Osunkoya, CS. Moreno, “Abstract LB466: Visium-HD spatial RNAseq analysis of aggressive prostatic adenocarcinoma identifies distinct RNA signatures in metastatic and non-metastatic disease”, Cancer Research, 85(8_Supplement_2):LB466–LB466, 2025
14. Z. Zhang, S. Azamat, X. Zheng, E. Kikano, C. Moreno, J. Yu, R. Shiradkar, M. Hajiha, M. Sanda, A. Madabhushi, “IP22-25 Prostanet: A Multi-scale 3D Feature Pyramid Network For Automatic Detection And Segmentation Of Clinically Significant Prostate Cancer On MRI”, Journal of Urology, 213(5S):e1178, 2025
15. A. Veldandi, E.L. Fogel, T. Tirkes, and R. Shiradkar, “Automated computation of semi-quantitative multi-parametric MRI (SQ-MRI) score using AI as a tool for evaluation of chronic pancreatitis”, American Pancreatic Association Annual Meeting, 2025
16. R. Chimmula, C. Yong, H. Love, R. Shiradkar, J. Holmes, C. Bahler, O. Oderinde, “Assessing the Predictive Accuracy of Radiogenomic Models Incorporating the Decipher Genomic Classifier and Radiomic Features for Biochemical Recurrence in Prostate Cancer”, International Journal of Radiation Oncology, Biology, Physics, 123(1):e588, 2025

Book Chapters

1. H.Kassem, A.Singh, A.Aristizabal, S.Bakas, M.Sheller, R.Umeton, S.Pati, P.N.Moorthy, A.Karargyris, “Collaborative evaluation for performance assessment of medical imaging applications”, Trustworthy AI in Medical Imaging, 2025, 978-0-443-23761-4

Pre-Prints

1. S. You, C. Pitarch-Abaigar, S. Kachole, S. Sonawane, J. Ha, AS. Gada, D. Crandall, R. Shiradkar, S.Bakas , “PROFUSEme: PROstate Cancer Biochemical Recurrence Prediction via FUSEd Multi-modal Embeddings”, arXiv preprint arXiv:250914051, 2025
2. J.S. Park, J. Ha, S. Thakur, A. Badea, S. Bakas, E. Garyfallidis, “Skull stripping with purely synthetic data”, 2025, arXiv preprint arXiv:2505.07159
3. D.LaBella, V.Abramova, M.Astaraki, A.Ferreira, Z.Jiang, M.C.Cleveland, R.Kang, U.M.L.Estrada, C.Yalcin, R.E.Hamadache, C.Lisazo, A.Casamitjana, J.Salvi, A.Oliver, X.Lladó, I.Toma-Dasu, T.Jesus, B.Puladi, J.Kleesiek, V.Alves, J.Egger, D.Capellán-Martín, A.Parida, A.Tapp, X.Liu, M.J.Ledesma-Carbayo, J.B.Patel, T.N.McNeal, M.Viera, O.McCall, A.E.Kim, E.R.Gerstner, C.P.Bridge, K.Schumacher, M.Mix, K.Leu, S.McBurney-Lin, P.Nedelec, J.Villanueva-Meyer, D.R.Raleigh, J.Shapey, T.Vercauteren, K.Chia, M.Ivory, T.Barfoot, O.Al-Salihi, J.Leu, L.M.Halasz, Y.S.Velichko, C.Wang, J.P.Kirkpatrick, S.R.Floyd, Z.J.Reitman, T.C.Mullikin, E.J.Vaios, C.Huang, U.Bagci, S.Sachdev, J.A.Hattangadi-Gluth, T.M.Seibert, N.Farid, C.Puett, M.W.Pease, K.Shiue, S.M.Anwar, S.Faghani, P.Taylor, P.Warman, J.Albrecht, A.Jakab, M.Moassefi, V.Chung, R.Chai, A.Aristizabal, A.Karargyris, H.Kassem, S.Pati, M.Sheller, N.Maleki, R.Saluja, F.Kofler, C.G.Schwarz, P.Lohmann, P.Vollmuth, L.Gagnon, M.Adewole, H.B.Li, A.F.Kazerooni, N.H.Tahon, U.Anazodo, A.W.Moawad, B.Menze, M.G.Linguraru, M.Aboian, B.Wiestler, U.Baid, G.Conte, A.M.Rauschecker, A.Nada, A.H.Abayazeed, R.Huang, M.C.d.Verdier, J.D.Rudie, S.Bakas, E.Calabrese, “Analysis of the 2024 BraTS Meningioma Radiotherapy Planning Automated Segmentation Challenge”, arXiv preprint arXiv: 2405.18383, 2025
4. A.Reinke, E.Christodoulou, S.Sadananda, A.E.Kavur, K.Faryna, D.Schouten, B.A.Landman, C.Sudre, O.Colliot, N.Heller, S.Loizillon, M.Maska, M.Solal, A.Yazdan-Panah, V.Bozgo, O.Sumer, S.de Jong, S.Fischer, M.Kozubek, T.Radsch, N.Hammoud, F.Molnar-Gabor, S.Hicks, M.A.Riegler, A.Saha, V.Thambawita, P.Halvorsen, A.Jimenez-Sanchez, Q.Yang, V.Cheplygina, S.Bottazzi, A.Seitel, S.Bakas, A.Karargyris, K.V.Venkadesh, B.van Ginneken, L.Maier-Hein, “Medical Imaging AI Competitions Lack Fairness”, arXiv preprint arXiv:2512.17581, 2025
5. R.Amiruddin, N.Y.Yordanov, N.Maleki, P.Fehringer, A.Gkampenis, A.Janas, K.Krantchev, A.Moawad, F.Umeh, S.Abosabie, S.Abosabie, A.Alotaibi, M.Ghonim, S.A.A.Mhana, N.Page, M.Jakovljevic, Y.Sharifi, P.Bhatia, A.Manteghinejad, M.Guelen, M.Veronesi, V.Hill, T.So, M.Krycia, B.Petrovic, F.Memon, J.Cramer, E.Schrickel, V.Kosovic, L.Vidal, G.Thompson, I.Ikuta, B.Albalooshy, A.Nabavizadeh, N.H.Tahon, K.Shekdar, A.Bhatia, C.Kirsch, G.D'Anna, P.Lohmann, A.S.Nour, A.Myronenko, A.Goldman-Yassen, J.R.Reid, S.Aneja, S.Bakas, M.Aboian, “Training the next generation of physicians for artificial intelligence-assisted clinical neuroradiology: ASNR MICCAI Brain Tumor Segmentation (BraTS) 2025 Lighthouse Challenge education platform”, arXiv preprint arXiv: 2509.17281, 2025
6. F.Kofler, M.Rosier, M.Astaraki, H.Möller, I.I.Mekki, J.A.Buchner, A.Schmick, A.Pfiffer, E.Oswald, L.Zimmer, E.de la Rosa, S.Pati, J.Canisius, U.Baid, M.Valizadeh, A.Linardos, J.C.Peeken, S.Shit, F.Steinbauer, D.Rueckert, R.Heckemann, S.Bakas, J.Kirschke, C.von See, I.Ezhov, M.Piraud, B.Wiestler, B.Menze, “BrainLesion Suite: A Flexible and User-Friendly Framework for Modular Brain Lesion Image Analysis”, arXiv preprint arXiv: 2507.09036, 2025
7. F.Kofler, M.Rosier, M.Astaraki, U.Baid, H.Möller, J.A.Buchner, F.Steinbauer, E.Oswald, E.de la Rosa, I.Ezhov, C.von See, J.Kirschke, A.Schmick, S.Pati, A.Linardos, C.Pitarch, S.Adap, J.Rudie, M.C.de Verdier, R.Saluja, E.Calabrese, D.LaBella, M.Aboian, A.W.Moawad, N.Maleki, U.Anazodo, M.Adewole, M.G.Linguraru, A.F.Kazerooni, Z.Jiang, G.M.Conte, H.Li, J.E.Iglesias, S.Bakas*, B.Wiestler*, M.Piraud*, B.Menze*, “BraTS orchestrator : Democratizing and Disseminating state-of-the-art brain tumor image analysis”, arXiv preprint arXiv: 2506.13807, 2025
8. S.Chadha, D.Weiss, A.Janas, D.Ramakrishnan, T.Hager, K.Osenberg, K.Willms, J.Zhu, V.Chiang, S.Bakas, N.Maleki, D.V.Sritharan, S.Schoenherr, M.Westerhoff, M.Zawalich, M.Davis, A.Malhotra, K.Bousabarah, C.Deuschl, M.D.Lin, S.Aneja, M.S.Aboian, “An 11,000-Study Open-Access Dataset of Longitudinal Magnetic Resonance Images of Brain Metastases”, arXiv preprint arXiv: 2506.14021, 2025
9. N.Maleki, R.Amiruddin, A.W.Moawad, N.Yordanov, A.Gkampenis, P.Fehringer, F.Umeh, C.Chukwurah, F.Memon, B.Petrovic, J.Cramer, M.Krycia, E.B.Shrickel, I.Ikuta, G.Thompson, L.Vidal, V.Kosovic, A.E.Goldman-Yassen, V.Hill, T.So, S.Mhana, A.Alotaibi, N.Page, P.Bhatia, Y.Sharifi, M.Jakovljevic, S.Abosabie, S.Abosabie, M.Ghonim, M.Ghonim, A.Manteghinejad, A.Janas, K.Krantchev, M.Adewole, J.Albrecht, U.Anazodo, S.Aneja, S.M.Anwar, T.Bergquist, V.Chiang, V.Chung, G.M.Conte, F.Dako, J.Eddy, I.Ezhov, N.Khalili, K.Farahani, J.E.Iglesias, Z.Jiang, E.Johanson, A.F.Kazerooni, F.Kofler, D.LaBella, K.V.Leemput, H.B.Li, M.G.Linguraru, X.Liu, Z.Meier, B.H.Menze, H.Moy, K.Osenberg, M.Piraud, Z.Reitman, R.T.Shinohara, C.Wang, B.Wiestler, W.Wiggins, U.Shafique, K.Willms, A.Avesta, K.Bousabarah, S.Chakrabarty, N.Gennaro, W.Holler, M.Kaur, P.LaMontagne, M.Lin, J.Lost, D.S.Marcus, R.Maresca, S.Merkaj, G.C.Pedersen, M.v.Reppert, A.Sotiras, O.Teytelboym, N.Tillmans, M.Westerhoff, A.Youssef, D.Godfrey, S.Floyd, A.Rauschecker, J.Villanueva-Meyer, I.Pflüger, J.Cho, M.Bendszus, G.Brugnara, G.J.G.Perez-Carillo, D.R.Johnson, A.Kam, B.Y.M.Kwan, L.Lai, N.U.Lall, S.N.Patro, L.Wu, A.Bansal, F.Barkhof, C.Besada, S.Chu, J.Druzgal, A.Dusoi, L.Farage, F.Feltrin, A.Fong, S.H.Fung, R.I.Gray, M.Iv, A.A.Postma, A.Mahajan, D.Joyner, C.Krumpelman, L.Letourneau-Guillon, C.M.Lincoln, M.E.Maros, E.Miller, F.Morón, E.A.Nimchinsky, O.Ozsarlak, U.Patel, S.Rohatgi, A.Saha, A.Sayah, E.D.Schwartz, R.Shih, M.S.Shiroishi, J.E.Small, M.Tanwar, J.Valerie, B.D.Weinberg, M.L.White, R.Young, V.M.Zohrabian, A.Azizova, M.M.T.Brüßeler, A.Okar, L.Pasquini, Y.Sharifi, G.Singh, N.Sollmann, T.Soumala, M.Taherzadeh, P.Vollmuth, M.Foltyn-Dumitru, A.Malhotra, F.Dellepiane, V.M.Pérez-García, H.Elhalawani, M.C.d.Verdier, S.A.Rubaiey, R.D.Armindo, K.Ashraf, M.M.Asla, M.Badawy, J.Bisschop, N.B.Lomer, J.Bukatz, J.Chen, P.Cimflova, F.Corr, A.Crawley, L.Deptula, T.Elakhdar, I.H.Shawali, S.Faghani, A.Frick, V.Gulati, M.A.Haider, F.Hierro, R.H.Dahl, S.M.Jacobs, K.J.Hsieh, S.G.Kandemirli, K.Kersting, L.Kida, S.Kollia, I.Koukoulithras, X.Li, A.Abouelatta, A.Mansour, R.Maria-Zamfirescu, M.Marsiglia, Y.S.Mateo-Camacho, M.McArthur, O.McDonnel, M.McHugh, M.Moassefi, S.M.Morsi, A.Munteanu, K.K.Nandolia, S.R.Naqvi, Y.Nikanpour, M.Alnoury, A.M.A.Nouh, F.Pappafava, M.D.Patel, S.Petrucci, E.Rawie, S.Raymond, B.Roohani, S.Sabouhi, L.M.S.Garcia, Z.Shaked, P.P.Suthar, T.Altes, E.Isufi, Y.Dhemesh, J.Gass, J.Thacker, A.R.Tarabishy, B.Turner, S.Vacca, G.K.Vilanilam, D.Warren, D.Weiss, F.Worede, S.Yousry, W.Lerebo, A.Aristizabal, A.Karargyris, H.Kassem, S.Pati, M.Sheller, K.E.Link, E.Calabrese, N.H.Tahon, A.Nada, J.D.Rudie, J.Reid, K.Darge, A.H.Abayazeed, P.Lohmann, Y.S.Velichko, S.Bakas, M.Aboian, “Analysis of the MICCAI Brain Tumor Segmentation -- Metastases (BraTS-METS) 2025 Lighthouse Challenge: Brain Metastasis Segmentation on Pre- and Post-treatment MRI”, arXiv preprint arXiv: 2504.12527, 2025.

Journal Manuscripts

1. H.Akbari, S.Bakas, C.Sako, A.Fathi Kazerooni, J.Villanueva-Meyer, J.A.Garcia, E.Mamourian, F.Liu, Q.Cao, R.T.Shinohara, U.Baid, A.Getka, S.Pati, A.Singh, E.Calabrese, S.Chang, J.Rudie, A.Sotiras, P.LaMontagne, D.S.Marcus, M.Milchenko, A.Nazeri, C.Balana, J.Capellades, J.Puig, C.Badve, J.S.Barnholtz-Sloan, A.E.Sloan, V.Vadmal, K.Waite, M.Ak, R.R.Colen, Y.W.Park, S.S.Ahn, J.H.Chang, Y.S.Choi, S.K.Lee, G.S.Alexander, A.S.Ali, A.P.Dicker, A.E.Flanders, S.Liem, J.Lombardo, W.Shi, G.Shukla, B.Griffith, L.M.Poisson, L.R.Rogers, A.Kotrotsou, T.C.Booth, R.Jain, M.Lee, A.Mahajan, A.Chakravarti, J.D.Palmer, D.DiCostanzo, H.Fathallah-Shaykh, S.Cepeda, O.S.Santonocito, A.L.Di Stefano, B.Wiestler, E.R.Melhem, G.F.Woodworth, P.Tiwari, P.Valdes, Y.Matsumoto, Y.Otani, R.Imoto, M.Aboian, S.Koizumi, K.Kurozumi, T.Kawakatsu, K.Alexander, L.Satgunaseelan, A.M.Rulseh, S.J.Bagley, M.Bilello, Z.A.Binder, S.Brem, A.S.Desai, R.A.Lustig, E.Maloney, T.Prior, N.Amankulor, M.P.Nasrallah, D.M.O’Rourke, S.Mohan, C.Davatzikos, ReSPOND consortium, "Machine learning-based prognostic subgrouping of glioblastoma: A multicenter study", Neuro-Oncology, noae260, 2024
2. V.S.Ahluwalia, N.Doiphode, W.C.Mankowski, E.A.Cohen, S.Pati, L.Pantalone, S.Bakas, A.Brooks, C.M.Vachon, E.F.Conant, A.Gastounioti, D.Kontos, "Volumetric Breast Density Estimation From Three-Dimensional Reconstructed Digital Breast Tomosynthesis Images Using Deep Learning", JCO Clinical Cancer Informatics, 8 (2024): e2400103, 2024
3. S.Bakas, P.Vollmuth, N.Galldiks, T.C.Booth, H.J.W.L.Aerts, W.L.Bi, B.Wiestler, P.Tiwari, S.Pati, U.Baid, E.Calabrese, P.Lohmann, M.Nowosielski, R.Jain, R.Colen, M.Ismail, G.Rasool, J.M.Lupo, H.Akbari, J.C.Tonn, D.Macdonald, M.Vogelbaum, S.M.Chang, C.Davatzikos, J.E.Villanueva-Meyer, R.Y.Huang, "Artificial Intelligence for Response Assessment in Neuro Oncology (AI-RANO), part 2: recommendations for standardisation, validation, and good clinical practice", The Lancet Oncology, 25(11), pp.e589-e601, 2024
4. J.E.Villanueva-Meyer, S.Bakas, P.Tiwari, J.M.Lupo, E.Calabrese, C.Davatzikos, W.L.Bi, M.Ismail, H.Akbari, P.Lohmann, T.C.Booth, B.Wiestler, H.J.W.L.Aerts, G.Rasool, J.C.Tonn, M.Nowosielski, R.Jain, R.R.Colen, S.Pati, U.Baid, P.Vollmuth, D.Macdonald, M.A.Vogelbaum, S.M.Chang, R.Y.Huang, N.Galldiks, "Artificial Intelligence for Response Assessment in Neuro Oncology (AI-RANO), part 1: review of current advancements", The Lancet Oncology, 25(11), pp.e581-e588, 2024
5. A.Afiaz, A.A.Ivanov, J.Chamberlin, D.Hanauer, C.L.Savonen, M.J.Goldman, M.Morgan, M.Reich, A.Getka, A.Holmes, S.Pati, D.Knight, P.C.Boutros, S.Bakas, J.G.Caporaso, G.Del Fiol, H.Hochheiser, B.Haas, P.D.Schloss, J.A.Eddy, J.Albrecht, A.Fedorov, L.Waldron, A.M.Hoffman, R.L.Bradshaw, J.T.Leek, C.Wright, "Best practices to evaluate the impact of biomedical research software—metric collection beyond citations", Bioinformatics, 40(8), btae469, 2024
6. S.Pati, S.Kumar, A.Varma, B.Edwards, C.Lu, L.Qu, J.J.Wang, A.Lakshminarayanan, S.Wang, M.J.Sheller, K.Chang, P.Singh, D.L.Rubin, J.Kalpathy-Cramer, S.Bakas, "Privacy Preservation for Federated Learning in Healthcare", Cell Patterns, Online, 2024
7. P.Whybra, A.Zwanenburg, V.Andrearczyk, R.Schaer, A.P.Apte, A.Ayotte, B.Baheti, S.Bakas, A.Bettinelli, R.Boellaard, L.Boldrini, I.Buvat, G.J.R.Cook, F.Dietsche, N.Dinapoli, H.S.Gabryś, V.Goh, M.Guckenberger, M.Hatt, M.Hosseinzadeh, A.Iyer, J.Lenkowicz, M.A.L.Loutfi, S.Löck, F.Marturano, O.Morin, C.Nioche, F.Orlhac, S.Pati, A.Rahmim, S.M.Rezaeijo, C.G.Rookyard, M.R.Salmanpour, A.Schindele, I.Shiri, E.Spezi, S.Tanadini-Lang, F.Tixier, T.Upadhaya, V.Valentini, J.J.M.van Griethuysen, F.Yousefirizi, H.Zaidi, H.Müller, M.Vallières, A.Depeursinge, "The image biomarker standardization initiative: Standardized convolutional filters for reproducible radiomics and enhanced clinical insights", Radiology, 310(2),e231319, 2024
8. B.Baheti, S.Innani, M.Nasrallah, S.Bakas, "Prognostic Stratification of Glioblastoma Patients by Unsupervised Clustering of Morphology Patterns on Whole Slide Images Furthering Our Disease Understanding", Frontiers in Neuroscience, 18, 1304191, 2024
9. D.Ramakrishnan, L.Jekel, S.Chadha, A.Janas, H.Moy, N.Maleki, M.Sala, M.Kaur, G.CassinelliPetersen, S.Merkaj, M.vonReppert, U.Baid, S.Bakas, C.Kirsch, M.Davis, K.Bousabarah, W.Holler, M.Lin, M.Westerhoff, S.Aneja, F.Memon, M.S.Aboian, "A large open access dataset of brain metastasis 3D segmentations on MRI with clinical and imaging information", Nature Scientific Data, 11(1), 254, 2024
10. B.Kocak, T.A.D’Antonoli, N.Mercaldo, A.Alberich Bayarri, B.Baessler, I.Ambrosini, A.E.Andreychenko, S.Bakas, R.G.H.Beets Tan, K.Bressem, I.Buvat, R.Cannella, L.A.Cappellini, A.U.Cavallo, L.L.Chepelev, L.C.H.Chu, A.Demircioglu, N.M.deSouza, M.Dietzel, S.C.Fanni, A.Fedorov, L.S.Fournier, V.Giannini, R.Girometti, K.B.W.G.Lipman, G.Kalarakis, B.S.Kelly, M.E.Klontzas, D. M.Koh, E.Kotter, H.Y.Lee, M.Maas, L.Marti Bonmati, H.Müller, N.Obuchowski, F.Orlhac, N.Papanikolaou, E.Petrash, E.Pfaehler, D.P.dosSantos, A.Ponsiglione, S.Sabater, F.Sardanelli, P.Seeböck, N.M.Sijtsema, A.Stanzione, A.Traverso, L.Ugga, M.Vallières, L.V.vanDijk, J.J.M.vanGriethuysen, R.W.vanHamersvelt, P.vanOoijen, F.Vernuccio, A.Wang, S.Williams, J.Witowski, Z.Zhang, A.Zwanenburg, R.Cuocolo, "METhodological RadiomICs Score (METRICS): A quality scoring tool for radiomics research endorsed by EuSoMII", Insights Into Imaging, 15(1):8, 2024
11. J.Guo, A.F.Kazerooni, E.Toorens, H.Akbari, F.Yu, C.Sako, E.Mamourian, R.T.Shinohara, C.Koumenis, S.J.Bagley, J.J.D.Morrissette, Z.A.Binder, S.Brem, S.Mohan, R.A.Lustig, D.M.O’Rourke, T.Ganguly, S.Bakas, M.P.Nasrallah, C.Davatzikos,, "Integrating imaging and genomic data for the discovery of distinct glioblastoma subtypes: a joint learning approach", Nature Scientific Reports, 14(1):4922, 2024
12. A.Reinke, M.D.Tizabi, M.Baumgartner, M.Eisenmann, D.Heckmann-Nötzel, A.E.Kavur, T.Rädsch, C.H.Sudre, L.Acion, M.Antonelli, T.Arbel, S.Bakas, A.Benis, F.Buettner, M.J.Cardoso, V.Cheplygina, J.Chen, E.Christodoulou, B.A.Cimini, K.Farahani, L.Ferrer, A.Galdran, B.v.Ginneken, B.Glocker, P.Godau, D.A.Hashimoto, M.M.Hoffman, M.Huisman, F.Isensee, P.Jannin, C.E.Kahn, D.Kainmueller, B.Kainz, A.Karargyris, J.Kleesiek, F.Kofler, T.Kooi, A.Kopp-Schneider, M.Kozubek, A.Kreshuk, T.Kurc, B.A.Landman, G.Litjens, A.Madani, K.Maier-Hein, A.L.Martel, E.Meijering, B.Menze, K.G.M.Moons, H.Müller, B.Nichyporuk, F.Nickel, J.Petersen, S.M.Rafelski, N.Rajpoot, M.Reyes, M.A.Riegler, N.Rieke, J.Saez-Rodriguez, C.I.Sánchez, S.Shetty, R.M.Summers, A.A.Taha, A.Tiulpin, S.A.Tsaftaris, B.v.Calster, G.Varoquaux, Z.R.Yaniv, P.F.Jäger, L.Maier-Hein,, "Understanding metric-related pitfalls in image analysis validation", Nature Methods, 21:182-194, 2024
13. L.Maier-Hein, A.Reinke, P.Godau, M.D.Tizabu, F.Buettner, E.Christodoulou, B.Glocker, F.Isensee, J.Kleesiek, M.Kozubek, M.Reyes, M.A.Riegler, M.Wiesenfarth, A.E.Kavur, C.H.Sudre, M.Baumgartner, M.Eisenmann, D.Heckmann-Nötzel, T.Rädsch, L.Acion, M.Antonelli, T.Arbel, S.Bakas, A.Benis, M.B.Blaschko, M.J.Cardoso, V.Cheplygina, B.Cimini, G.S.Collins, K.Farahani, L.Ferrer, A.Galdran, B.van Ginneken, R.Haase, D.A.Hashimoto, M.M.Hoffman, M.Huisman, P.Jannin, C.E.Kahn, D.Kainmueller, B.Kainz, A.Karargyris, A.Karthikesalingam, F.Kofler, A.Kopp-Schneider, A.Kreshuk, T.Kurc, B.A.Landman, G.Litjens, A.Madani, K.Maier-Hein, A.L.Martel, P.Mattson, E.Meijering, B.Menze, K.G.M.Moons, H.Müller, B.Nichyporuk, F.Nickel, J.Petersen, N.Rajpoot, N.Rieke, J.Saez-Rodriguez, C.I.Sanchez, S.Shetty, M.van Smeden, R.M.Summers, A.A.Taha, A.Tiulpin, S.A.Tsaftaris, B.V.Calster, G.Varoquaux, P.F.Jäger,, "Metrics reloaded: Recommendations for image analysis validation", Nature Methods, 21(2):195-212, 2024
14. D.LaBella, O.Khanna, S.McBurney-Lin, R.Mclean, P.Nedelec, A.S.Rashid, N.H.Tahon, T.Altes, U.Baid, R.Bhalerao, Y.Dhemesh, F.Hilal, A.Janas, A.Fathi Kazerooni, C.Kent, J.Kirkpatrick, F.Kofler, K.Leu, N.Maleki, B.Menze, M.Pajot, Z.J.Reitman, J.D.Rudie, R.Saluja, Y.Velichko, C.Wang, P.I.Warman, N.Sollmann, D.Diffley, K.K.Nandolia, D.I.Warren, A.Hussain, J.P.Fehringer, Y.Bronstein, L.Deptula, E.G.Stein, M.Taherzadeh, E.P.de Oliveira, A.Haughey, M.Kontzialis, L.Saba, B.Turner, M.M.T.Brüßeler, S.Ansari, A.Gkampenis, D.M.Weiss, A.Mansour, I.H.Shawali, N.Yordanov, J.M.Stein, R.Hourani, M.Y.Moshebah, A.M.Abouelatta, T.Rizvi, K.Willms, D.C.Martin, A.Okar, G.D’Anna, A.Taha, Y.Sharifi, S.Faghani, D.Kite, M.Pinho, M.A.Haider, M.Alonso-Basanta, J.Villanueva-Meyer, A.M.Rauschecker, A.Nada, M.Aboian, A.Flanders, S.Bakas*, E.Calabrese*,, "A Multi-Institutional Meningioma MRI Dataset for Automated Multi-Sequence Image Segmentation", Nature Scientific Data, 11(1):496, 2024
15. M.G.Linguraru, S.Bakas, M.Aboian, P.Chang, A.Flanders, J.Kalpathy-Cramer, F.C.Kitamura, M.Lungren, J.Mongan, L.Prevedello, R.M.Summers, C.C.Wu, M.Adewole, C.E.Kahn,, "Clinical, Cultural, Computational, and Regulatory Considerations to Deploy AI in Radiology: Perspectives of RSNA and MICCAI Experts”", Radiology: Artificial Intelligence, 6(4), 2024
16. G.Yang, B.Edwards, S.Bakas, Q.Dou, D.Xu, X.Li, W.Wang,, "Federated learning as a catalyst for digital healthcare innovations", Cell Patterns, 5(7):101026, 2024S.Gongala, J.Garcia, N.Korakavi, N.Patil, H.Akbari, C.Tippareddy, A.Sloan, J.Barnholtz-Sloan, S.Bakas, A.Fathi Kazerooni, C.Sako, U.Baid, S.Brem, R.A Lustig, J.Capellades, M.Nasrallah, D.M O'Rourke, P.LaMontagne, D.S Marcus, C.Balana, J.Puig, K.Waite, R.Colen, Y.Seong Choi, S.Lee, A.P Dicker, A.E Flanders, W.Shi, B.Griffith, L.M Poisson, L.R Rogers, T.C Booth, R.Jain, A.Chakravarti, J.Palmer, S.Mohan, P.Tiwari, M.Aboian, S.Soo Ahn, C.Davatzikos, C.Badve,, "Sex-specific differences in glioblastoma in the ReSPOND consortium", American Journal of NeuroRadiology, 45(9):1299-1307, 2024
17. F.Gomez, A.M.Danos, G.Del Fiol, A.Madabhushi, P.Tiwari, J.F.McMichael, S.Bakas, J.Bian, C.Davatzikos, E.J.Fertig, J.Kalpathy-Cramer, J.Kenney, G.Savova, M.Yetisgen, E.M.Van Allen, J.L.Warner, F.Prior, M.Griffith, O.L.Griffith,, "A new era of data-driven cancer research and care: opportunities and challenges", Cancer Discovery, 14(10):1774-1778, 2024
18. J.L.Agraz, C.Agraz, A.A.Chen, C.Rice, R.S.Pozos, S.Aelterman, A.Tan, A.N.Viaene, M.P.Nasrallah, P.Sharma, C.M.Grenko, T.Kurc, J.Saltz, M.D.Feldman, H.Akbari, R.T.Shinohara, S.Bakas, P.Wilson,, "Optimized Whole-Slide-Image H&E Stain Normalization: A Step Towards Big Data Integration in Digital Pathology", IEEE Open Journal of Engineering in Medicine and Biology, 6:35-40, 2024
19. J.Lost, N.Ashraf, L.Jekel, M.v.Reppert, N.Tillmanns, K.Willms, S.Merkaj, G.C.Petersen, A.Avesta, D.Ramakrishnan, A.Omuro, A.Nabavizadeh, S.Bakas, M.Lin, S.Aneja, M.Sabel, M.Aboian,, "Enhancing Clinical Decision-Making: An Externally Validated Machine Learning Model for Predicting IDH Mutation in Gliomas using Radiomics from Pre-Surgical MRI", NeuroOncology Advances, 6(1), 2024
20. T.M.Malta, T.S.Sabedot, N.S.Morosini, I.Datta, L.Garofano, W.Vallentgoed, F.S.Varn, K.Aldape, F.D’Angelo, S.Bakas, J.S.Barnholtz-Sloan, H.K.Gan, M.Hasanain, A.-C.Hau, K.C.Johnson, M.Khasraw, E.Kocakavuk, M.C.M.Kouwenhoven, S.Migliozzi, S.P.Niclou, J.M.Niers, D.R.Ormond, S.H.Paek, G.Reifenberger, P.A.S.Smitt, M.Smits, L.F.Stead, M.J.van den Bent, E.G.V.Meir, A.Walenkamp, T.Weiss, M.Weller, B.A.Westerman, B.Ylstra, P.Wesseling, A.Lasorella, P.J.French, L.M.Poisson, R.G.W.Verhaak, A.Iavarone, H.Noushmehr, "The epigenetic evolution of gliomas is determined by their IDH1 mutation status and treatment regimen", Cancer Research, 84(5):741-756, 2024, 2024

Peer Reviewed Full-length Conference Articles

1. I.E.Hamamci, S.Er, A.Sekuboyina, E.Simsar, A.Tezcan, A.G.Simsek, S.N.Esirgun, F.Almas, I.Dogan, M.F.Dasdelen, C.Prabhakar, H.Reynaud, S.Pati, C.Bluethgen, M.K.Ozdemir, B.Menze, "Generatect: Text-conditional generation of 3d chest ct volumes", ECCV, pp. 126-143, 2024
2. S.Innani, B.Baheti, M.P.Nasrallah, S.Bakas, "Weakly Supervised IDH-status glioma classification from H&E-stained whole slide images", ISBI 2024, Athens, Greece, Online, 2024
3. S.Innani, M.P.Nasrallah,W.R.Bell, B.Baheti, S.Bakas, "Multi-scale Whole Slide Image Assessment Improves Deep Learning based WHO 2021 Glioma Classification", MICCAI COMPAYL Workshop 2024, Marrakesh, Morocco, Online, 2024
4. N.Doiphode, V.S.Ahluwalia, W.C.Mankowski, E.A.Cohen, S.Pati, L.Pantalone, S.Bakas, A.Brooks, C.M.Vachon, E.F.Conant, A.Gastounioti, D.Kontos,, "Advancing volumetric breast density segmentation: a deep learning approach with digital breast tomosynthesis", In Proc. 17th Int Workshop on Breast Imaging (IWBI), 13174:131740O, 2024
5. S.Adap, U.Baid, S.Bakas, "Classifying Histopathologic Glioblastoma Sub-regions with EfficientNet", MICCAI Consolidated Brain Analytics Satellite Events Proceedings,, [In Press], , 2024
6. P.Liang, H.Zheng, H.Li, Y.Gong, S.Bakas, Y.Fan,, "Enhancing Whole Slide Image Classification with Discriminative and Contrastive Learning", International Conference on Medical Image Computing and Computer-Assisted Intervention, Springer LNCS, 15004:102-112, 2024
7. D.Waldmannstetter, B.Wiestler, J.Schwarting, I.Ezhov, M.Metz, S.Bakas, B.Baheti, S.Chakrabarty, D.Rueckert, J.S.Kirschke, R.A.Heckemann, M.Piraud, B.H.Menze, F.Kofler, , "Primitive Simultaneous Optimization of Similarity Metrics for Image Registration", Springer - MICCAI BrainLes - LNCS, 14668:57-68, 2024
8. U.Baid, S.Pati, T.M.Kurc, R.Gupta, E.Bremer, S.Abousamra, S.P.Thakur, J.H.Saltz, S.Bakas., "Pan-Cancer Tumor Infiltrating Lymphocyte Detection based on Federated Learning", In IEEE Int. Conf. on Big Data, pp. 7640-7647, 2024
   
   

Abstracts

1. S.Innani, B.Baheti, M.P.Nasrallah, W.R.Bell, S.Bakas, "PATH-39. AI-based identification of glioma IDH mutational status from H&E-stained whole slide images", Neuro-Oncology, 26, Supplement_8, Page viii187, 2024
2. A.Janas, A.Gkampenis, N.Yordanov, P.Fehringer, K.Krantchev, A.W.Moawad, U.Baid, K.E.Link, Y.S.Velichko, D.LaBella, F.Kofler, E.Calabrese, U.Shafique, G.Conte, R.Saluja, N.H.Tahon, N.Maleki, A.Abayazeed, S.Aneja, A.Nada, H.Li, M.Foltyn, S.Bakas, J.Rudie, BraTS-METS Challenge 2023 Group, M.Aboian, , "A novel approach concerning medical education on AI and ML through the ASNR MICCAI BraTS 2023 brain metastases challenge", Neuro-Oncology, 26(Suppl_5):v55, 2024
3. H.Akbari, S.Mohan, A.F.Kazerooni, S.Rathore, M.Bilello, C.Sako, J.Garcia, C.Jiang, F.Liu, M.Berger, S.Brem, S.Bakas, E.Mamourian, A.Pepin, P.James, J.Dorsey, A.Singh, D.Parker, R.Verma, Q.Cao, R.T.Shinohara, S.J.Bagley, A.Desai, D.M.O’Rourke, M.Nasrallah, M.Alonso-Basanta, B.-K.K.Teo, G.Kurtz, G.Shukla, R.A.Lustig, C.Davatzikos,, "AI-Guided Personalized Precision Radiation Therapy With Targeted Dose Esalation for Newly Diagnosed Glioblastoma: A Matched-Control Study", Neuro-Oncology, 26(Suppl_8):viii103-viii103, 2024
4. S.Mohan, J.Garcia, H.Akbari, S.Kwak, K.Baik, M.Shalaby, Y.Matsumoto, S.Bakas, P.Kamel, C.Tippareddy, C.Badve, M.Lee, J.Barnholtz-Sloan, A.Sloan, A.Chakravarti, J.Palmer, A.Dicker, A.Flanders, W.Shi, R.Jain, P.LaMontagne, D.Marcus, A.Sotiras, C.Balana, J.Capellades, J.Puig, S.Cepeda, A.L.D.Stefano, B.Wiestler, G.Woodworth, D.ORourke, M.Nasrallah, C.Davatzikos,, "Multi-Institutional Validation of an AI-based Model for Prediction of Tumor Infiltration and Future Recurrence in Patients with Glioblastoma: Results from the ReSPOND Consortium", Neuro-Oncology, 26(Suppl_8):viii205-viii206, 2024
5. J.Guo, A.Fathi-Kazerooni, E.Toorens, H.Akbari, F.Yu, Y.Matsumoto, C.Sako, E.Mamourian, R.Shinohara, C.Koumenis, I.Verginadis, S.Bagley, J.Morrissette, Z.Binder, S.Brem, S.Mohan, R.Lustig, D.O’Rourke, T.Ganguly, S.Bakas, M.Aboian, M.Nasrallah, C.Davatzikos,, "Subtyping Glioblastoma from Joint Clustering of Imaging and Genomic Data", Neuro-Oncology, 26(Suppl_8):viii209-viii209, 2024
6. S.Thakur, S.Faghani, M.Moassefi, U.Baid, V.Chung, S.Pati, S.Innani, B.Baheti, J.Albrecht, A.Karargyris, H.Kassem, M.Nasrallah, J.Ahrendsen, V.Barresi, M.Gubbiotti, G.Lopez, C.-H.Lucas, M.Miller, L.Cooper, J.Huse, W.R.Bell, S.Bakas, "BraTS-Path: Assessing Heterogenenous Histopathologic Regions in Glioblastoma", Neuro-Oncology, 26(Suppl_8):viii312-viii312, 2024

Journal Manuscripts

1. L.Maier-Hein, A.Reinke, P.Godau, M.D.Tizabu, F.Buettner, E.Christodoulou, B.Glocker, F.Isensee, J.Kleesiek, M.Kozubek, M.Reyes, M.A.Riegler, M.Wiesenfarth, A.E.Kavur, C.H.Sudre, M.Baumgartner, M.Eisenmann, D.Heckmann-Nötzel, T.Rädsch, L.Acion, M.Antonelli, T.Arbel, S.Bakas, A.Benis, M.B.Blaschko, M.J.Cardoso, V.Cheplygina, B.Cimini, G.S.Collins, K.Farahani, L.Ferrer, A.Galdran, B.van Ginneken, R.Haase, D.A.Hashimoto, M.M.Hoffman, M.Huisman, P.Jannin, C.E.Kahn, D.Kainmueller, B.Kainz, A.Karargyris, A.Karthikesalingam, F.Kofler, A.Kopp-Schneider, A.Kreshuk, T.Kurc, B.A.Landman, G.Litjens, A.Madani, K.Maier-Hein, A.L.Martel, P.Mattson, E.Meijering, B.Menze, K.G.M.Moons, H.Müller, B.Nichyporuk, F.Nickel, J.Petersen, N.Rajpoot, N.Rieke, J.Saez-Rodriguez, C.I.Sanchez, S.Shetty, M.van Smeden, R.M.Summers, A.A.Taha, A.Tiulpin, S.A.Tsaftaris, B.V.Calster, G.Varoquaux, P.F.Jäger, “Metrics reloaded: Recommendations for image analysis validation”, Nature Methods, [In Press] (arXiv preprint arXiv:2206.01653), 2023

2. A.Reinke, M.D.Tizabi, M.Baumgartner, M.Eisenmann, D.Heckmann-Nötzel, A.E.Kavur, T.Rädsch, C.H.Sudre, L.Acion, M.Antonelli, T.Arbel, S.Bakas, A.Benis, F.Buettner, M.J.Cardoso, V.Cheplygina, J.Chen, E.Christodoulou, B.A.Cimini, K.Farahani, L.Ferrer, A.Galdran, B.v.Ginneken, B.Glocker, P.Godau, D.A.Hashimoto, M.M.Hoffman, M.Huisman, F.Isensee, P.Jannin, C.E.Kahn, D.Kainmueller, B.Kainz, A.Karargyris, J.Kleesiek, F.Kofler, T.Kooi, A.Kopp-Schneider, M.Kozubek, A.Kreshuk, T.Kurc, B.A.Landman, G.Litjens, A.Madani, K.Maier-Hein, A.L.Martel, E.Meijering, B.Menze, K.G.M.Moons, H.Müller, B.Nichyporuk, F.Nickel, J.Petersen, S.M.Rafelski, N.Rajpoot, M.Reyes, M.A.Riegler, N.Rieke, J.Saez-Rodriguez, C.I.Sánchez, S.Shetty, R.M.Summers, A.A.Taha, A.Tiulpin, S.A.Tsaftaris, B.v.Calster, G.Varoquaux, Z.R.Yaniv, P.F.Jäger, L.Maier-Hein, “Understanding metric-related pitfalls in image analysis validation”, Nature Methods, [In Press] (arXiv preprint arXiv:2302.01790), 2023.

3. C.G.Filippi, J.M.Stein, Z.Wang, S.Bakas, Y.Liu, P.D.Chang, Y.Lui, C.Hess, D.P.Barboriak, A.E.Flanders, M.Wintermark, G.Zaharchuk, O.Wu, “Ethical Considerations and Fairness in the Use of Artificial Intelligence for Neuroradiology”, AJNR Am. J. Neuroradiol., 44(11):1242-1248, 2023

4. J.Lost, T.Verma, L.Jekel, M.v.Reppert, N.Tillmanns, S.Merkaj, G.C.Petersen, R.Bahar, A.Gordem, M.A.Haider, H.Subramanian, W.Brim, I.Ikuta, A.Omuro, G.M.Conte, B.V.Marquez-Nostra, A.Avesta, K.Bousabarah, A.Nabavizadeh, A.F.Kazerooni, S.Aneja, S.Bakas, M.Lin, M.Sabel, M.Aboian, “Systematic Literature Review of Machine Learning Algorithms Using Pre-Therapy Radiological Imaging for Glioma Molecular Subtype Prediction”, AJNR Am. J. Neuroradiol., (Online ahead of print), 2023

5. T.M.Malta, T.S.Sabedot, N.S.Morosini, I.Datta, L.Garofano, W.Vallentgoed, F.S.Varn, K.Aldape, F.D’Angelo, S.Bakas, J.S.Barnholtz-Sloan, H.K.Gan, M.Hasanain, A.-C.Hau, K.C.Johnson, M.Khasraw, E.Kocakavuk, M.C.M.Kouwenhoven, S.Migliozzi, S.P.Niclou, J.M.Niers, D.R.Ormond, S.H.Paek, G.Reifenberger, P.A.S.Smitt, M.Smits, L.F.Stead, M.J.van den Bent, E.G.V.Meir, A.Walenkamp, T.Weiss, M.Weller, B.A.Westerman, B.Ylstra, P.Wesseling, A.Lasorella, P.J.French, L.M.Poisson, R.G.W.Verhaak, A.Iavarone, H.Noushmehr, “The epigenetic evolution of gliomas is determined by their IDH1 mutation status and treatment regimen”, Cancer Research [Online ahead of print], 2023. doi: 10.1158/0008-5472.CAN-23-2093.

6. P.Whybra, A.Zwanenburg, V.Andrearczyk, R.Schaer, A.P.Apte, A.Ayotte, B.Baheti, S.Bakas, A.Bettinelli, R.Boellaard, L.Boldrini, I.Buvat, G.J.R.Cook, F.Dietsche, N.Dinapoli, H.S.Gabryś, V.Goh, M.Guckenberger, M.Hatt, M.Hosseinzadeh, A.Iyer, J.Lenkowicz, M.A.L.Loutfi, S.Löck, F.Marturano, O.Morin, C.Nioche, F.Orlhac, S.Pati, A.Rahmim, S.M.Rezaeijo, C.G.Rookyard, M.R.Salmanpour, A.Schindele, I.Shiri, E.Spezi, S.Tanadini-Lang, F.Tixier, T.Upadhaya, V.Valentini, J.J.M.v.Griethuysen, F.Yousefirizi, H.Zaidi, H.Müller, M.Vallières, A.Depeursinge, “The Image Biomarker Standardization Initiative: Standardized convolutional filters for quantitative radiomics”, arXiv preprint arXiv:2006.05470, Radiology (In Press), 2023

7. S.Innani, P.Dutande, U.Baid, V.Pokuri, S.Bakas, S.Talbar, B.Baheti, S.C.Guntuku, “Generative adversarial networks based skin lesion segmentation”, Nature Scientific Reports, 13:13467, 2023.

8. S.M.Rezaeijo, N.Chegeni, F.B.Naeini, D.Makris, S.Bakas, “Within-Modality Synthesis and Novel Radiomic Evaluation of Brain MRI Scans”, Cancers, 15(14), 2023.

9. M.D.Lee, S.H.Patel, S.Mohan, H.Akbari, S.Bakas, M.P.Nasrallah, E.Calabrese, J.Rudie, J.Villanueva-Meyer, P.LaMontagne, D.S.Marcus, R.R.Colen, C.Balana, Y.S.Choi, C.Badve, J.S.Barnholtz-Sloan, A.E.Sloan, T.C.Booth, J.D.Palmer, A.P.Dicker, A.E.Flanders, W.Shi, B.Griffith, L.M.Poisson, A.Chakravarti, A.Mahajan, S.Chang, D.Orringer, C.Davatzikos, R.Jain, “Association of partial T2-FLAIR mismatch sign and isocitrate dehydrogenase mutation in WHO grade 4 gliomas: results from the ReSPOND consortium”, Neuroradiology, 65:1343–1352, 2023.\

10. A. Karargyris, R. Umeton, M. Sheller, A. Aristizabal, J. George, A. Wuest, S. Pati, H. Kassem, M. Zenk, U. Baid, P. N. Moorthy, A. Cowdhury, J. Guo, S. Nalawade, J. Rsenthal, D. Kanter, M. Xenochristou, D. Beutel, V. Chung, T. Bergquist , J. Eddy, A. Abid, L. Tunstall, O. Sanseviero, D. Dimitriadis, Y. Qian, X. Xu, Y. Lio, R. S.M. Goh, S. Bala, V. Bittorf, S. R. Puchala, B. Riciuti, S. Samineni, E. Sengupta, A. Chaudhari, C. Coleman, B. Desinghu, G. Diamos, D. Dutta, D. Feddema, G. Fursin, X. Huang, S. Kashyap, N. Lane, I. Mallick, F. Consortium, B. Consortium, A. Consortium, C. Consortium,, P. Mascagni, V. Mehta, C. F. Moraes, V. Natarajan, N. Nikolov, N. Padoy, G. Pekhimenko, V. J. Reddi , G. A. Reina, P. Ribalta, A. Sing, J. J. Thiagarajana, J. Albrecht, T. Wolf, G. Miller, H. Fu, P. Shah, D. Xu, P. Yadav, D. Talby, M. M. Awad, J. P. Howard, M. Rosenthal, L. Marchionni, M. Loda, J. M. Johnson, P. Mattson*, S. Bakas*, “Federated Benchmarking of Medical Artificial Intelligence with MedPerf”, Nature Machine Intelligence, 5:799–810, 2023.

11. S.Pati, S.P.Thakur, I.E.Hamamci, U.Baid, B.Baheti, M.Bhalerao, O.Guley, S.Mouchtaris, D.Lang, S.Thermos, K.Gotkowski, C.Gonzalez, C.Grenko, A.Getka, B.Edwards, M.Sheller, J.Wu, D.Karkada, R.Panchumarthy, V.Ahluwalia, C.Zou, V.Bashyam, Y.Li, B.Haghighi, R.Chitalia, S.Abousamra, T.M.Kurc, A.Gastounioti, S.Er, M.Bergman, J.H.Saltz, Y.Fan, P.Shah, A.Mukhopadhyay, S.A.Tsaftaris, B.Menze, C.Davatzikos, D.Kontos, A.Karargyris, R.Umeton, P.Mattson, S.Bakas, “GaNDLF: The Generally Nuanced Deep Learning Framework for Scalable End-to-End Clinical Workflows”, Nature Communications Engineering, 2(1), 2023.

12. F.Kofler, I.Ezhov, F.Isensee, F.Balsiger, C.Berger, M.Koerner, B.Demiray, J.Rackerseder, J.Paetzold, H.Li, S.Shit, R.McKinley, M.Piraud, S.Bakas, C.Zimmer, N.Navab, J.Kirschke, B.Wiestler, B.H.Menze, “Are we using appropriate segmentation metrics? Identifying correlates of human expert perception for CNN training beyond rolling the DICE coefficient”, Journal of Machine Learning for Biomedical Imaging (MELBA), 2, 2023:002, 2023.

13. B.Kocak*, B.Baessler*, S.Bakas*, R.Cuocolo, A.Fedorov, L.Maier-Hein, N.Mercaldo, H.Muller, F.Orlhac, D.P.Santos, A.Stanzione, L.Ugga, A.Zwanenburg, “CheckList for EvaluAtion of Radiomics research (CLEAR): a step-by-step reporting guideline for authors and reviewers endorsed by ESR and EuSoMII”, Insights Into Imaging, 14(75), 2023.

14. Z.R.Samani, D.Parker, H.Akbari, R.L.Wolf, S.Brem, S.Bakas, R.Verma, “Artificial intelligence-based locoregional markers of brain peritumoral microenvironment”, Nature Scientific Reports, 13(1):963, 2023.

15. R.Dorent, A.Kujawa, M.Ivory, S.Bakas, N.Rieke, S.Joutard, B.Glocker, J.Cardoso, M.Modat, K.Batmanghelich, A.Belkov, M.B.Calisto, J.W.Choi, B.M.Dawant, H.Dong, S.Escalera, Y.Fan, L.Hansen, M.P.Heinrich, S.Joshi, V.Kashtanova, H.G.Kim, S.Kondo, C.N.Kruse, S.K.Lai-Yuen, H.Li, H.Liu, B.Ly, I.Oguz, H.Shin, B.Shirokikh, Z.Su, G.Wang, J.Wu, Y.Xu, K.Yao, L.Zhang, S.Ourselin, J.Shapey, T.Vercauteren, ”CrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwnannoma and Cochlea Segmentation”, Medical Image Analysis, 83, 102628, 2023.

Full-length peer-reviewed conference papers

M.Eisenmann, A.Reinke, V.Weru, M.D.Tizabi, F.Isensee, T.J.Adler, S.Ali, V.Andrearczyk, M.Aubreville, U.Baid, S.Bakas, N.Balu, S.Bano, J.Bernal, S.Bodenstedt, A.Casella, V.Cheplygina, M.Daum, M.de Bruijne , A.Depeursinge, R.Dorent, J.Egger, D.G.Ellis, S.Engelhardt, M.Ganz, N.Ghatwary, G.Girard, P.Godau, A.Gupta, L.Hansen, K.Harada, M.Heinrich, N.Heller, A.Hering, A.Huaulmé, P.Jannin, A.E.Kavur, O.Kodym, M.Kozubek, J.Li, H.Li, J.Ma, C.Martín-Isla, B.Menze, A.Noble, V.Oreiller, N.Padoy, S.Pati, K.Payette, T.Rädsch, J.Rafael-Patiño, V.Singh Bawa, S.Speidel, C.H.Sudre, K.van Wijnen, M.Wagner, D.Wei, A.Yamlahi, M.Yap, C.Yuan, M.Zenk, A.Zia, D.Zimmerer, D.Aydogan, B.Bhattarai, L.Bloch, R.Brüngel, J.Cho, C.Choi, Q.Dou, I.Ezhov, C.M.Friedrich, C.Fuller, R.R.Gaire, A.Galdran, Á.García Faura, M.Grammatikopoulou, S.Hong, M.Jahanifar, I.Jang, A.Kadkhodamohammadi, I.Kang, F.Kofler, S.Kondo, H.Kuijf, M.Li, M.Luu, T.Martinčič, P.Morais, M.A.Naser, B.Oliveira, D.Owen, S.Pang, J.Park, S.Park, S.Płotka, E.Puybareau, N.Rajpoot, K.Ryu, N.Saeed, A.Shephard, P.Shi, D.Štepec, R.Subedi, G.Tochon, H.R.Torres, H.Urien, J.L.Vilaça, K.A.Wahid, H.Wang, J.Wang, L.Wang, X.Wang, B.Wiestler, M.Wodzinski, F.Xia, J.Xie, Z.Xiong, S.Yang, Y.Yang, Z.Zhao, K.Maier-Hein, P.F.Jäger, A.Kopp-Schneider, L.Maier-Hein, “Why is the winner the best?”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), [In Press], 2023 [arXiv preprint arXiv:2303.17719]

Abstracts

1. B.Baheti, S.Innani, G.Mehdiratta, M.P.Nasrallah, S.Bakas, “Interpretable whole slide image prognostic stratification of glioblastoma patients furthering current disease understanding”, Neuro-Oncology, 25(Suppl.2):ii103-ii104, 2023.

2. B.Baheti, S.Innani, M.P.Nasrallah, S.Bakas, “A unsupervised clustering of morphology patterns on whole slide images guide prognostic stratification of glioblastoma patients”, Neuro-Oncology, 25(Suppl.2):ii15, 2023. [Oral Presentation at EANO 2023]

3. S.Pati, U.Baid, B.Edwards, M.Sheller, J.Martin, A.Karargyris, S.Bakas, “The Comprehensive Open Federated Ecosystem (COFE): Enabling impactful healthcare studies”, Pendergrass Symposium (University of Pennsylvania, Philadelphia, PA USA), June 2023. (Plenary session: higher distinction than Summa Cum Laude)

4. B.Baheti, S.Innani, G.Mehdiratta, M.P.Nasrallah,S.Bakas, “Interpretable whole slide image prognostic stratification of glioblastoma patients furthering current clinical knowledge”, 19th European Congress on Digital Pathology (ECDP), 2023.

5. B.Baheti, S.Innani, M.P.Nasrallah, S.Bakas, “Unsupervised clustering of morphology patterns on whole slide images guide prognostic stratification of glioblastoma patients”, 19th European Congress on Digital Pathology (ECDP), 2023.

6. S.Pati, S.Bakas, “Federated Learning and Reproducibility in Healthcare”, Proceedings of the Dagstuhl Seminar Series, 2023

7. S.Innani, B.Baheti, M.P.Nasrallah, S.Bakas, "Interpretable IDH classification from H&E-stained histology slides", Neuro-Oncology, Volume 25, Issue Supplement_5, November 2023, Page v177, https://doi.org/10.1093/neuonc/noad179.0669

8. B.Baheti, S.Rai, S.Innani, G.Mehdiratta, S.C.Guntuku, M.P.Nasrallah, S.Bakas, "Detecting Histologic & Clinical Glioblastoma Patterns Of Prognostic Relevance", Neuro-Oncology, Volume 25, Issue Supplement_5, November 2023, Page v126, https://doi.org/10.1093/neuonc/noad179.0478

Book chapter

A.Gastounioti, O.H.Maghsoudi, S.Rathore, E.F.Conant, D.Kontos, S.Bakas. Chapter: Computational Applications in Brain and Breast Cancer, “Book: State of the Art in Neural Networks”, Elsevier, 2023.

Citable data repositories

D.Ramakrishnan, L.Jekel, S.Chadha, A.Janas, H.Moy, N.Maleki, M.Sala, M.Kaur, G.C.Petersen, S.Merkaj, M.vonReppert, U.Baid, S.Bakas, C.Kirsch, M.Davis, K.Bousabarah, W.Holler, M.Lin, M.Westerhoff, S.Aneja, F.Memon, M.S.Aboian, “A Large Open Access Dataset of Brain Metastasis 3D Segmentations on MRI with Clinical and Imaging Feature Information (Version 1) [dataset]”. The Cancer Imaging Archive, 2023. DOI: https://doi.org/10.7937/6be1-r748

E-books

M.E.Celebi, M.S.Salekin, H.Kim, S.Albarqouni, C.Barata, A.Halpern, P.Tschandl, M.Combalia, Y.Liu, G.Zamzmi, J.Levy, H.Rangwala, A.Reinke , D.Wynn, B.Landman, W.-K.Jeong, Y.Shen, Z.Deng, S.Bakas, X.Li, C.Qin, N.Rieke, H.Roth, D.Xu, “Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 Workshops”, ISIC 2023, Care-AI 2023, MedAGI 2023, DeCaF 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8–12, 2023, Proceedings, Lecture Notes in Computer Science book series (LNCS 14393)