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Shubham Innani

portrait of Shubham Innani

Education
BTech in Electronics and Telecommunication Engineering – SGGS IET, Nanded, India – 2020

Titles and Appointments
Research Analyst

Address
HITS Building
410 W 10th Street
Indianapolis, IN 46202

Research Keywords
Digital Pathology, Deep Learning/Machine Learning, Interpretability, Biomarkers, Survival.

Links
Google Scholar
LinkedIn
Twitter
GitHub
Personal Website
orcid

Professional Organizations/Memberships
MICCAI Society

Research Summary/Bio
Shubham Innani is a research analyst in the Division of Computational Pathology engaged in pioneering research focusing on the development of computational algorithms. His primary focus centers on driving advancements in digital pathology, seamlessly integrating technology and health care. His research interest currently focuses on the exploration of histopathological images driving advancements in interpretability, survival prediction, and biomarker identification. Through his dedicated efforts, Shubham contributes significantly to advancing our understanding of complex medical data, paving the way for innovative solutions in the field of medical imaging. With an academic foundation and a keen eye for emerging trends, his commitment to pushing the boundaries of computational pathology exemplifies a forward-thinking approach that promises to shape the future landscape of medical research.

Featured publications

  • Bhakti Baheti, Sunny Rai, Shubham Innani, Garv Mehdiratta, Sharath Chandra Guntuku, MacLean P. Nasrallah, and Spyridon Bakas. "Detecting Histologic & Clinical Glioblastoma Patterns of Prognostic Relevance." (2023) arXiv preprint arXiv:2302.00669.