HealthContradict: Evaluating biomedical knowledge conflicts in language models - Top-Institutions - MDSpire

HealthContradict: Evaluating biomedical knowledge conflicts in language models

  • By

  • Boya Zhang

  • Alban Bornet

  • Rui Yang

  • Nan Liu

  • Douglas Teodoro

  • January 21, 2026

  • 0 min

Share

Top Institutions in General Medicine

Brief introduction explaining scope and methodology.

  • #1

    Stanford University
    Stanford University

    Stanford, CA

    Key Differentiators

    • Biomedical Informatics
    • Artificial Intelligence
    • Computer Science

  • #2

    Massachusetts Institute of Technology (MIT)
    Massachusetts Institute of Technology (MIT)

    Cambridge, MA

    Key Differentiators

    • Artificial Intelligence
    • Biomedical Engineering
    • Computer Science

  • #3

    Johns Hopkins University
    Johns Hopkins University

    Baltimore, MD

    Key Differentiators

    • Biomedical Informatics
    • Health Data Science
    • Artificial Intelligence

  • #4

    University of California, San Francisco (UCSF)
    University of California, San Francisco (UCSF)

    San Francisco, CA

    Key Differentiators

    • Biomedical Informatics
    • Clinical AI
    • Health Data Science

  • #5

    University of Washington
    University of Washington

    Seattle, WA

    Key Differentiators

    • Biomedical Informatics
    • Artificial Intelligence
    • Health Informatics

Original Source(s)

HealthContradict: Evaluating biomedical knowledge conflicts in language models

  • by Boya Zhang, Alban Bornet, Rui Yang, Nan Liu, Douglas Teodoro

  • January 21, 2026

Related Content

Defining operational safety in clinical artificial intelligence systems

Interoperable Integration of a National Rare Disease Registry Into a Rare Eye Disease Data Warehouse: Implementation Study

Benchmarking large language model-based agent systems for clinical decision tasks