Uncertainty-Informed Deep Learning Models Enable High-Confidence Predictions for Digital Histopathology. - James M. Dolezal; Andrew Srisuwananukorn; Dmitry Karpeyev; Siddhi Ramesh; Sara Kochanny; Brittany Cody; Aaron Mansfield; Sagar Rakshit; Radhika Bansa; Melanie Bois; Aaron O. Bungum; Jefree J. Schulte; et al. (CoRR, 2022)

Deep Learning Generates Synthetic Cancer Histology for Explainability and Education. - James M. Dolezal; Rachelle Wolk; Hanna M. Hieromnimon; Frederick M. Howard; Andrew Srisuwananukorn; Dmitry Karpeyev; Siddhi Ramesh; Sara Kochanny; Jung Woo Kwon; Meghana Agni; Richard C. Simon; Chandni Desai; et al. (CoRR, 2022)

Slideflow: Deep Learning for Digital Histopathology with Real-Time Whole-Slide Visualization. - James M. Dolezal; Sara Kochanny; Emma C. Dyer; Andrew Srisuwananukorn; Matteo Sacco; Frederick M. Howard; Anran Li 007; Prajval Mohan; Alexander T. Pearson (CoRR, 2023)

Slideflow: deep learning for digital histopathology with real-time whole-slide visualization. - James M. Dolezal; Sara Kochanny; Emma C. Dyer; Siddhi Ramesh; Andrew Srisuwananukorn; Matteo Sacco; Frederick M. Howard; Anran Li 007; Prajval Mohan; Alexander T. Pearson (BMC Bioinform., 2024)