James M Dolezal

9PUBLICATIONS
35CO-AUTHORS
Adversarial machine learningDeep learningPredictive and prognostic markersHaematological tumours
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Publications (9)

|Nov 15, 2024
Generative adversarial networks accurately reconstruct pan-cancer histology from pathologic, genomic, and radiographic latent features.

Frederick M Howard, Hanna M Hieromnimon, Siddhi Ramesh

|Nov 07, 2024
Artificial intelligence-based morphologic classification and molecular characterization of neuroblastic tumors from digital histopathology.

Siddhi Ramesh, Emma Dyer, Monica Pomaville

|Apr 14, 2023
Integration of clinical features and deep learning on pathology for the prediction of breast cancer recurrence assays and risk of recurrence.

Frederick M Howard, James Dolezal, Sara Kochanny

|Feb 15, 2023
Machine learning for detection and classification of oral potentially malignant disorders: A conceptual review.

Lucas Lacerda de Souza, Felipe Paiva Fonseca, Anna Luiza Damaceno Araújo

|Nov 03, 2022
Uncertainty-informed deep learning models enable high-confidence predictions for digital histopathology.

James M Dolezal, Andrew Srisuwananukorn, Dmitry Karpeyev

|Dec 10, 2020
Deep learning prediction of BRAF-RAS gene expression signature identifies noninvasive follicular thyroid neoplasms with papillary-like nuclear features.

James M Dolezal, Anna Trzcinska, Chih-Yi Liao

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Frequent Collaborators

6 joint publications

Alexander T Pearson

2 joint publications

Andrew Srisuwananukorn

2 joint publications

Charles M Perou

2 joint publications

Galina Khramtsova