57 citations · 79 across the 5 of their papers we have counts for
5 papers
A Multimodal Foundation Model for Longitudinal Patient Representation and Scalable Insight Generation in Oncology
Eugene Vorontsov, Yi Kan Wang, Alican Bozkurt +13
Precision oncology necessitates a longitudinal model of patient state that captures cancer evolution and treatment over time, integrating multimodal observations. We introduce the…
PRISM2: Unlocking Multi-Modal General Pathology AI with Clinical Dialogue
Eugene Vorontsov, George Shaikovski, Adam Casson +16
Recent rapid progress in the field of computational pathology has been enabled by foundation models. These models are beginning to move beyond encoding image patches towards whole-…
Screen Them All: High-Throughput Pan-Cancer Genetic and Phenotypic Biomarker Screening from H&E Whole Slide Images
Yi Kan Wang, Ludmila Tydlitatova, Jeremy D. Kunz +15
Molecular assays are standard of care for detecting genomic alterations in cancer prognosis and therapy selection but are costly, tissue-destructive and time-consuming. Artificial…
PRISM: A Multi-Modal Generative Foundation Model for Slide-Level Histopathology
George Shaikovski, Adam Casson, Kristen Severson +19
Foundation models in computational pathology promise to unlock the development of new clinical decision support systems and models for precision medicine. However, there is a misma…
Virchow: A Million-Slide Digital Pathology Foundation Model
Eugene Vorontsov, Alican Bozkurt, Adam Casson +28
The use of artificial intelligence to enable precision medicine and decision support systems through the analysis of pathology images has the potential to revolutionize the diagnos…