Interpretable artificial intelligence based determination of glioma IDH mutation status directly from histology slides
Accurate H&E-based determination of glioma IDH mutation status can expedite conclusive diagnosis and clinical decision-making and even facilitate it in underserved regions. Finally, interpretability analysis of distilled human-identifiable features can further improve our understanding of the disease.
Authors
- Shubham Innani (ORCID: https://orcid.org/0000-0003-3616-0308)
- Spyridon Bakas (ORCID: https://orcid.org/0000-0001-8734-6482)
- Bhakti Baheti (ORCID: https://orcid.org/0000-0001-5475-3903)
- MacLean P. Nasrallah (ORCID: https://orcid.org/0000-0003-4861-0898)
- Hannah J. Harmsen (ORCID: https://orcid.org/0000-0003-2634-0321)
- William R. Bell (ORCID: https://orcid.org/0000-0001-6326-3885)
Institutions
- Indiana University Health (US)
- Indiana Cancer Consortium (US)
- Neurological Surgery (US)
- Indiana University Melvin and Bren Simon Comprehensive Cancer Center
- Indiana University School of Medicine
- Indiana University – Purdue University Indianapolis (US)
- University of Pennsylvania (US)
Publication Details
- Journal
- Neuro-Oncology Advances
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1093/noajnl/vdaf140
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.36