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Showing 1–7 of 7 results
Advanced filters: Author: Juraj Gottweis Clear advanced filters

  • With an improved framework for model development and evaluation, a large language model is shown to provide answers to medical questions that are comparable or preferred with respect to those provided by human physicians.

    • Karan Singhal
    • Tao Tu
    • Vivek Natarajan
    ResearchOpen Access
    Nature Medicine
    Volume: 31, P: 943-950

  • Diagnostic reasoning using an optimized large language model with a dataset comprising real-world medical cases exhibited improved differential diagnostic performance as an assistive tool for clinicians over search engines and standard medical resources.

    • Daniel McDuff
    • Mike Schaekermann
    • Vivek Natarajan
    ResearchOpen Access
    Nature
    Volume: 642, P: 451-457

  • The conversational diagnostic artificial intelligence system AMIE (Articulate Medical Intelligence Explorer) has potential as a real-world tool for clinical history-taking and diagnostic dialogue, based on its performance in simulated consultations.

    • Tao Tu
    • Mike Schaekermann
    • Vivek Natarajan
    ResearchOpen Access
    Nature
    Volume: 642, P: 442-450

  • Our ability to use engineered bacteria for cancer therapy is rapidly expanding. A survey of preclinical, clinical and commercial efforts provides an overview of the state of the field, revealing trends that could inform future directions.

    • Edward R. Ballister
    • Alexander Michels
    • Tal Danino
    Comments & Opinion
    Nature Biotechnology
    Volume: 43, P: 672-676

  • Med-PaLM, a state-of-the-art large language model for medicine, is introduced and evaluated across several medical question answering tasks, demonstrating the promise of these models in this domain.

    • Karan Singhal
    • Shekoofeh Azizi
    • Vivek Natarajan
    ResearchOpen Access
    Nature
    Volume: 620, P: 172-180

  • Patient notes contain shorthand and abbreviations that may be jargon or clinical vernacular. Here the authors train large machine learning models on public web data to decode such text by replacing abbreviations with their meanings.

    • Alvin Rajkomar
    • Eric Loreaux
    • Juraj Gottweis
    ResearchOpen Access
    Nature Communications
    Volume: 13, P: 1-14