138 citations · 142 across the 2 of their papers we have counts for
2 papers
eess.IV2022★ 4 cited
Deep Learning Generates Synthetic Cancer Histology for Explainability and Education
James M. Dolezal, Rachelle Wolk, Hanna M. Hieromnimon +20
Artificial intelligence methods including deep neural networks (DNN) can provide rapid molecular classification of tumors from routine histology with accuracy that matches or excee…
q-bio.QM2022★ 138 cited
Uncertainty-Informed Deep Learning Models Enable High-Confidence Predictions for Digital Histopathology
James M Dolezal, Andrew Srisuwananukorn, Dmitry Karpeyev +13
A model's ability to express its own predictive uncertainty is an essential attribute for maintaining clinical user confidence as computational biomarkers are deployed into real-wo…