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Medical, health, and genomics

Digital pathology helps decode tumor microenvironments for precision immunotherapy. GigaPath is a novel vision transformer that can scale to gigapixel whole-slide images by adapting dilated attention for digital pathology. In joint work with Providence and UW, we’re sharing Prov-GigaPath, the first whole-slide pathology foundation model pretrained on large-scale real-world data, for advancing clinical research and discovery.

GigaPath: Whole-Slide Foundation Model for Digital Pathology

Research Forum Ep2 | Panel | Transforming the Natural Sciences with AI

Research Forum 2 | Panel Discussion: Transforming the Natural Sciences with AI

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Scaling early detection of esophageal cancer with AI

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Microsoft Health Futures

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Video

AI for Precision Health: Learning the language of nature and patients

February 25, 2025 | Hoifung Poon, Ava Amini, Lili Qiu, Matthew Lungren, Carlo Bifulco

Hosted by Hoifung Poon, with Lili Qiu, Ava Amini, Carlo Bifulco (opens in new tab), and Matthew Lungren at Microsoft Research Forum, Episode 5 This panel discussion with Microsoft researchers and external guests explores the transformative potential of generative AI in…

44:59

Video

Keynote: Multimodal Generative AI for Precision Health

February 25, 2025 | Hoifung Poon

Presented by Hoifung Poon at Microsoft Research Forum, Episode 5 Hoifung Poon, General Manager of Microsoft Health Futures, introduces an agenda in precision health, utilizing generative AI to pretrain high-fidelity patient embeddings from multimodal, longitudinal patient journeys. This…

17:14

Event

Microsoft Research Forum

February 25, 2025 | Virtual

Microsoft Research Forum Location: Virtual Register for the series Microsoft Research Forum is a virtual series highlighting purposeful research and its real-world impact, from fundamental exploration to advancing AI responsibly, scaling innovation through products and…

Research Forum | abstract background with colorful hexagons

Publication

Consequences of training data composition for deep learning models in single-cell biology

Ajay Nadig, Akshaya Thoutam, Madeline Hughes, Anay Gupta, Andrew W. Navia, Nicolo Fusi, Srivatsan Raghavan, Peter S. Winter, Ava P. Amini, Lorin Crawford

bioRxiv | February 2025

Project

Microsoft Research Blog

Exploring the structural changes driving protein function with BioEmu-1

February 20, 2025 | Sarah Lewis, Tim Hempel, Jose Jimenez-Luna, Michael Gastegger, Yu Xie, Victor García Satorras, Osama Abdin, Bas Veeling, Ryota Tomioka, Frank Noé

Meet BioEmu-1 from Microsoft Research. This deep learning model can generate thousands of protein structures per hour, unlocking new possibilities for protein scientists and drug discovery and research.