138 citations · 150 across the 4 of their papers we have counts for
4 papers
Toward Quantum-Enabled Biomarker Discovery: An Outlook from Q4Bio
Dhirpal Shah, Mariesa Teo, Ryan A. Robinett +12
We present a case study and forward-looking perspective on co-design for hybrid quantum-classical algorithms, centered on the goal of empirical quantum advantage (EQA), which we de…
Slideflow: Deep Learning for Digital Histopathology with Real-Time Whole-Slide Visualization
James M. Dolezal, Sara Kochanny, Emma Dyer +6
Deep learning methods have emerged as powerful tools for analyzing histopathological images, but current methods are often specialized for specific domains and software environment…
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…
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…