illustration of DNA strand and abstract shapes on a computer screen on a green gradient background

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

white icons of first aid kit, DNA strand, laptop monitor with overlapping eye, and microscope on a blue and green gradient background

Scaling early detection of esophageal cancer with AI

female doctor / nurse reviewing a tablet

Microsoft Health Futures

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Publication

Learnings from a Large-Scale Deployment of an LLM-Powered Expert-in-the-Loop Healthcare Chatbot

Bhuvan Sachdeva, Pragnya Ramjee, Geeta Fulari, Dr. Kaushik Murali, Mohit Jain

September 2024

Project Project

Microsoft Research Blog

MedFuzz: Exploring the robustness of LLMs on medical challenge problems

September 10, 2024 | Robert Osazuwa Ness

Medfuzz tests LLMs by breaking benchmark assumptions, exposing vulnerabilities to bolster real-world accuracy.

Publication

Overview of ImageCLEFmedical 2024 – Caption Prediction and Concept Detection

Johannes Rückert, Asma Ben Abacha, Alba G. Seco de Herrera, Louise Bloch, Raphael Brüngel, Ahmad Idrissi-Yaghir, Henning Schäfer, Benjamin Bracke, Hendrik Damm, Tabea M. G. Pakull, Cynthia Sabrina Schmidt, Henning Müller, Christoph M. Friedrich

CLEF 2024 Conference and Labs of the Evaluation Forum | September 2024

Publication

Overview of the MEDIQA-MAGIC Task at ImageCLEF 2024: Multimodal And Generative TelemedICine in Dermatology

Wen-wai Yim, Asma Ben Abacha, Yujuan Fu, Zhaoyi Sun, Meliha Yetisgen, Fei Xia

CLEF 2024 Conference and Labs of the Evaluation Forum | September 2024

Video

CataractBot: An LLM-Powered Experts-in-the-Loop Chatbot for Cataract Patients

September 3, 2024

Patients need reliable health information, but the digital age overwhelms them with excess and often inaccurate information. Patients trust medical professionals the most, but time constraints restrict this communication. To bridge this gap, we at…

03:45

Video

Panel: Beyond Language: The future of multimodal models in healthcare, gaming, and AI

September 3, 2024 | John Langford, Katja Hofmann, Jianwei Yang, Hoifung Poon

Microsoft researchers discuss the transformative potential and core challenges of multimodal models across various domains, including precision health, game intelligence, and foundation models. Microsoft researchers will share their thoughts on future directions, bridging gaps, and…

59:42

Publication

Performance of explainable artificial intelligence in guiding the management of patients with a pancreatic cyst

Juan M. Lavista Ferres, Felipe Oviedo, Caleb Robinson, Linda Chu, Satomi Kawamoto , Elham Afghani, Jin He, Alison P Klein, Mike Goggins, Christopher L Wolfgang, Ammar A Javed, Rahul Dodhia, Nick Papadopolous, Ken Kinzler, Ralph H Hruban, Bill Weeks, Elliot K Fishman, Anne Marie Lennon

Pancreatology | September 2024

Project

Tool

RadFact

RadFact is a framework for the evaluation of model-generated radiology reports given a ground-truth report, with or without grounding. Leveraging the logical inference capabilities of large language models, RadFact is not a single number but…

GitHub

Publication

A Methodology for Using Large Language Models to Create User-Friendly Applications for Medicaid Redetermination and Other Social Services

Sumanth Ratna, Bill Weeks, Juan M. Lavista Ferres, Aneesh Chopra, Mayana Pereira

International Journal of Public Health | August 2024

Project

Microsoft Research Blog

Large-scale pathology foundation models show promise on a variety of cancer-related tasks

August 8, 2024 | Kristen Severson, Philip Rosenfield

Microsoft researchers collaborated to release new pathology foundation models. Their report shows models benefit from diverse data, increased model size, and specialized algorithms to enhance the accuracy and applicability of cancer diagnosis and treatment.

Medical, health, and genomics

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