8 citations · 14 across the 4 of their papers we have counts for
4 papers
PLUTO-4: Frontier Pathology Foundation Models
Harshith Padigela, Shima Nofallah, Atchuth Naveen Chilaparasetti +11
Foundation models trained on large-scale pathology image corpora have demonstrated strong transfer capabilities across diverse histopathology tasks. Building on this progress, we i…
Learning biologically relevant features in a pathology foundation model using sparse autoencoders
Nhat Minh Le, Ciyue Shen, Neel Patel +13
Pathology plays an important role in disease diagnosis, treatment decision-making and drug development. Previous works on interpretability for machine learning models on pathology…
PLUTO: Pathology-Universal Transformer
Dinkar Juyal, Harshith Padigela, Chintan Shah +30
Pathology is the study of microscopic inspection of tissue, and a pathology diagnosis is often the medical gold standard to diagnose disease. Pathology images provide a unique chal…
Rethinking Machine Learning Model Evaluation in Pathology
Syed Ashar Javed, Dinkar Juyal, Zahil Shanis +3
Machine Learning has been applied to pathology images in research and clinical practice with promising outcomes. However, standard ML models often lack the rigorous evaluation requ…