6 papers
A Foundation Model for Spatial Proteomics
Muhammad Shaban, Yuzhou Chang, Huaying Qiu +57
Foundation models have begun to transform image analysis by acting as pretrained generalist backbones that can be adapted to many tasks even when post-training data are limited, ye…
Accelerating Data Processing and Benchmarking of AI Models for Pathology
Andrew Zhang, Guillaume Jaume, Anurag Vaidya +2
Advances in foundation modeling have reshaped computational pathology. However, the increasing number of available models and lack of standardized benchmarks make it increasingly c…
Molecular-driven Foundation Model for Oncologic Pathology
Anurag Vaidya, Andrew Zhang, Guillaume Jaume +15
Foundation models are reshaping computational pathology by enabling transfer learning, where models pre-trained on vast datasets can be adapted for downstream diagnostic, prognosti…
Multimodal Whole Slide Foundation Model for Pathology
Tong Ding, Sophia J. Wagner, Andrew H. Song +20
The field of computational pathology has been transformed with recent advances in foundation models that encode histopathology region-of-interests (ROIs) into versatile and transfe…
Multistain Pretraining for Slide Representation Learning in Pathology
Guillaume Jaume, Anurag Vaidya, Andrew Zhang +7
Developing self-supervised learning (SSL) models that can learn universal and transferable representations of H&E gigapixel whole-slide images (WSIs) is becoming increasingly valua…
MedCalc-Bench: Evaluating Large Language Models for Medical Calculations
Nikhil Khandekar, Qiao Jin, Guangzhi Xiong +14
As opposed to evaluating computation and logic-based reasoning, current benchmarks for evaluating large language models (LLMs) in medicine are primarily focused on question-answeri…