283 citations · 579 across the 9 of their papers we have counts for
10 papers
Accelerating Scientific Research with Gemini in the Real-World
Samuel Schmidgall, Xiaokai Zhu, Marian Shaw +32
We present an extension and comprehensive real-world validation of Co-Scientist, a Gemini-based multi-agent system designed to accelerate end-to-end scientific research across hypo…
MedGemma 1.5 Technical Report
Andrew Sellergren, Chufan Gao, Fereshteh Mahvar +39
We introduce MedGemma 1.5 4B, the latest model in the MedGemma collection. MedGemma 1.5 expands on MedGemma 1 by integrating additional capabilities: high-dimensional medical imagi…
PolyPath: Adapting a Large Multimodal Model for Multi-slide Pathology Report Generation
Faruk Ahmed, Lin Yang, Tiam Jaroensri +11
The interpretation of histopathology cases underlies many important diagnostic and treatment decisions in medicine. Notably, this process typically requires pathologists to integra…
Health AI Developer Foundations
Atilla P. Kiraly, Sebastien Baur, Kenneth Philbrick +23
Robust medical Machine Learning (ML) models have the potential to revolutionize healthcare by accelerating clinical research, improving workflows and outcomes, and producing novel…
PathAlign: A vision-language model for whole slide images in histopathology
Faruk Ahmed, Andrew Sellergren, Lin Yang +14
Microscopic interpretation of histopathology images underlies many important diagnostic and treatment decisions. While advances in vision-language modeling raise new opportunities…
Domain-specific optimization and diverse evaluation of self-supervised models for histopathology
Jeremy Lai, Faruk Ahmed, Supriya Vijay +13
Task-specific deep learning models in histopathology offer promising opportunities for improving diagnosis, clinical research, and precision medicine. However, development of such…
Graph Neural Networks for Image Classification and Reinforcement Learning using Graph representations
Naman Goyal, David Steiner
In this paper, we will evaluate the performance of graph neural networks in two distinct domains: computer vision and reinforcement learning. In the computer vision section, we see…
Predicting Prostate Cancer-Specific Mortality with A.I.-based Gleason Grading
Ellery Wulczyn, Kunal Nagpal, Matthew Symonds +20
Gleason grading of prostate cancer is an important prognostic factor but suffers from poor reproducibility, particularly among non-subspecialist pathologists. Although artificial i…
Interpretable Survival Prediction for Colorectal Cancer using Deep Learning
Ellery Wulczyn, David F. Steiner, Melissa Moran +20
Deriving interpretable prognostic features from deep-learning-based prognostic histopathology models remains a challenge. In this study, we developed a deep learning system (DLS) f…
Deep learning-based survival prediction for multiple cancer types using histopathology images
Ellery Wulczyn, David F. Steiner, Zhaoyang Xu +7
Prognostic information at diagnosis has important implications for cancer treatment and monitoring. Although cancer staging, histopathological assessment, molecular features, and c…