645 citations · 1.2k across the 25 of their papers we have counts for
26 papers
Beyond Sparse Captions: Aligning Slide-Level Text and Patch-Level Vision in Pathology
Daniel Shao, Dongmin Bang, Luca L. Weishaupt +6
Contrastive vision-language (VL) pretraining in computational pathology has generally relied on curated image-caption datasets sourced from social media, educational videos, and re…
A multimodal and temporal foundation model for virtual patient representations at healthcare system scale
Andrew Zhang, Tong Ding, Sophia J. Wagner +8
Modern medicine generates vast multimodal data across siloed systems, yet no existing model integrates the full breadth and temporal depth of the clinical record into a unified pat…
From Query to Counsel: Structured Reasoning with a Multi-Agent Framework and Dataset for Legal Consultation
Mingfei Lu, Yi Zhang, Mengjia Wu +1
Legal consultation question answering (Legal CQA) presents unique challenges compared to traditional legal QA tasks, including the scarcity of high-quality training data, complex t…
Do Multiple Instance Learning Models Transfer?
Daniel Shao, Richard J. Chen, Andrew H. Song +4
Multiple Instance Learning (MIL) is a cornerstone approach in computational pathology (CPath) for generating clinically meaningful slide-level embeddings from gigapixel tissue imag…
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…
Evidence-based diagnostic reasoning with multi-agent copilot for human pathology
Luca L. Weishaupt, Chengkuan Chen, Drew F. K. Williamson +8
Pathology is experiencing rapid digital transformation driven by whole-slide imaging and artificial intelligence (AI). While deep learning-based computational pathology has achieve…