Join the ARISE mailing list to stay updated on healthcare AI research →

Advancing Healthcare AI
Through Open Science Research

ARISE brings together researchers across institutions at the intersection of medicine, technology, and real-world impact.

See our Medical AI Superintelligence Test (MAST), which is in preview↗

Insights

Industry Report · 2026

Healthcare AI
Industry Report

Practical guidance for industry leaders as healthcare AI moves toward deployment at scale.

2026 Healthcare AI Industry Report cover

Featured Work

Explore our tools and prototypes designed to advance clinical AI research and practice.

Medical AI Superintelligence Test (MAST)

Our benchmark for evaluating the clinical accuracy and safety of frontier medical AI models, currently in preview.

ARISEKit

Our open-source toolkit for the clinical AI research community, available on GitHub.

First Do NOHARM

A specialist-validated benchmark towards deploying clinically accurate and safe models.

Discover Benchmark

Featured Blog Posts

Insights, perspectives, and updates from the ARISE research community.

ARISE Launches Research Collaboration with Grow Therapy to Benchmark AI Safety in Mental Health Conversations

ARISE Launches Research Collaboration with Grow Therapy to Benchmark AI Safety in Mental Health Conversations

Jul 14, 2026

ARISE awarded $3.8M ARPA-H funding to advance physician-AI collaboration in medicine

ARISE awarded $3.8M ARPA-H funding to advance physician-AI collaboration in medicine

May 19, 2026

Public Trust Remains The Limiting Factor For AI Adoption In U.S. Healthcare

Public Trust Remains The Limiting Factor For AI Adoption In U.S. Healthcare

Jan 18, 2026

Latest Research

Our research focuses on how clinical AI should be evaluated, trusted, and used in real care.

SycoEval-EM: Sycophancy Evaluation of Large Language Models in Simulated Clinical Encounters for Emergency Care

SycoEval-EM: Sycophancy Evaluation of Large Language Models in Simulated Clinical Encounters for Emergency Care

PreprintJul 7, 2026

Screening for Missed Opportunities for Diagnosis in the ED Using eTriggers and Large Language Models

Screening for Missed Opportunities for Diagnosis in the ED Using eTriggers and Large Language Models

JAMA Network OpenJun 29, 2026

Evaluating the robustness and readiness of large frontier models in health AI applications

Evaluating the robustness and readiness of large frontier models in health AI applications

Nature MedicineJun 26, 2026

Large reasoning models as thinking machines for medicine

Large reasoning models as thinking machines for medicine

Nature Biomedical EngineeringJun 23, 2026

SycoEval-EM: Sycophancy Evaluation of Large Language Models in Simulated Clinical Encounters for Emergency Care

SycoEval-EM: Sycophancy Evaluation of Large Language Models in Simulated Clinical Encounters for Emergency Care

PreprintJul 7, 2026

Screening for Missed Opportunities for Diagnosis in the ED Using eTriggers and Large Language Models

Screening for Missed Opportunities for Diagnosis in the ED Using eTriggers and Large Language Models

JAMA Network OpenJun 29, 2026

Evaluating the robustness and readiness of large frontier models in health AI applications

Evaluating the robustness and readiness of large frontier models in health AI applications

Nature MedicineJun 26, 2026

Large reasoning models as thinking machines for medicine

Large reasoning models as thinking machines for medicine

Nature Biomedical EngineeringJun 23, 2026

SycoEval-EM: Sycophancy Evaluation of Large Language Models in Simulated Clinical Encounters for Emergency Care

SycoEval-EM: Sycophancy Evaluation of Large Language Models in Simulated Clinical Encounters for Emergency Care

PreprintJul 7, 2026

Screening for Missed Opportunities for Diagnosis in the ED Using eTriggers and Large Language Models

Screening for Missed Opportunities for Diagnosis in the ED Using eTriggers and Large Language Models

JAMA Network OpenJun 29, 2026

Evaluating the robustness and readiness of large frontier models in health AI applications

Evaluating the robustness and readiness of large frontier models in health AI applications

Nature MedicineJun 26, 2026

Large reasoning models as thinking machines for medicine

Large reasoning models as thinking machines for medicine

Nature Biomedical EngineeringJun 23, 2026

Latest News

Get the latest on our studies, grant awards, and media coverage.

How A.I. Might Change the Way Doctors Think

How A.I. Might Change the Way Doctors Think

New York TimesJul 1, 2026

When AI Makes the Call, Doctors May Take the Blame

When AI Makes the Call, Doctors May Take the Blame

MedscapeJun 24, 2026

AI Is Taking Over Hospitals

AI Is Taking Over Hospitals

The AtlanticJun 17, 2026

Inside the Trump-backed push to bring AI doctors into American medicine

Inside the Trump-backed push to bring AI doctors into American medicine

The Washington PostJun 4, 2026

Did AI Really Beat ER Doctors At Diagnosis? Here’s What The Study Showed

Did AI Really Beat ER Doctors At Diagnosis? Here’s What The Study Showed

ForbesMay 22, 2026

AI doctors should be licensed. Here’s a framework to do that

AI doctors should be licensed. Here’s a framework to do that

STAT NewsMay 11, 2026

Investigators

We bring together clinicians, researchers, and technical experts to study how AI can be safely and meaningfully integrated into healthcare.

Ethan Goh

Ethan Goh

Stanford University, Executive Director

Adam Rodman

BIDMC / Harvard University, Site Lead

Jonathan H Chen

Jonathan H Chen

Stanford University, Site Lead

Arjun Manrai

Arjun Manrai

Harvard University, Site Lead

Eric Horvitz

Eric Horvitz

Microsoft, Stanford University

Neera Ahuja

Neera Ahuja

Stanford University

Vishnu Ravi

Vishnu Ravi

Stanford University, Technical Director

Jason Hom

Jason Hom

Stanford University