David A. Gutman

Evaluating the Transferability of Pathology Foundation Models Across Cancer-related H&E Neurodegeneration-related Immunohistochemical Classification Tasks

This study evaluates how well frozen pathology foundation models transfer to cancer-related H&E and neurodegenerative IHC tasks, finding better performance on H&E tasks than on specialized IHC tasks.

Neuromorphological changes following selection for tameness and aggression in the Russian fox-farm experiment

The paper reports neural morphology changes in foxes selected for tameness or aggression, finding similar brain volume increases in both groups compared to unselected foxes.

Predicting cancer outcomes from histology and genomics using convolutional networks

This study uses deep learning to predict cancer patient outcomes by integrating histology images and genomic data, showing improved performance over current clinical methods for glioma survival prediction.

Interactive Phenotyping Of Large-Scale Histology Imaging Data With HistomicsML

HistomicsML enables interactive machine learning for analyzing histology images to identify phenotypes and predict survival in gliomas.

Predicting clinical outcomes from large scale cancer genomic profiles with deep survival models

This paper applies deep learning and Bayesian optimization to predict cancer clinical outcomes from genomic data, showing improved prognostic accuracy through transfer learning and providing an open-source framework.