Stanford Medicine

Large Language Model Influence on Diagnostic Reasoning

Ethan Goh, Robert Gallo, Jason Hom et al.

2024 · 496 Zit.

Testing and Evaluation of Health Care Applications of Large Language Models

Suhana Bedi, Yutong Liu, Lucy Orr-Ewing et al.

2024 · 391 Zit.

Shifting machine learning for healthcare from development to deployment and from models to data

Angela Zhang, Lei Xing, James Zou et al.

2022 · 388 Zit.

Lack of Transparency and Potential Bias in Artificial Intelligence Data Sets and Algorithms

Roxana Daneshjou, Mary P. Smith, Mary Sun et al.

2021 · 353 Zit.

Large language models propagate race-based medicine

Jesutofunmi A. Omiye, Jenna Lester, Simon Spichak et al.

2023 · 329 Zit.

Almanac — Retrieval-Augmented Language Models for Clinical Medicine

Cyril Zakka, Rohan Shad, Akash Chaurasia et al.

2024 · 317 Zit.

Explainable artificial intelligence models using real-world electronic health record data: a systematic scoping review

Seyedeh Neelufar Payrovnaziri, Zhaoyi Chen, Pablo Rengifo‐Moreno et al.

2020 · 307 Zit.

The TRIPOD-LLM reporting guideline for studies using large language models

Jack Gallifant, Majid Afshar, Saleem Ameen et al.

2025 · 305 Zit.

Ethical and regulatory challenges of large language models in medicine

Jasmine Chiat Ling Ong, Yin‐Hsi Chang, William Wasswa et al.

2024 · 255 Zit.

Diagnostic reasoning prompts reveal the potential for large language model interpretability in medicine

Thomas Savage, Ashwin Nayak, Robert Gallo et al.

2024 · 219 Zit.

Artificial Intelligence–Generated Draft Replies to Patient Inbox Messages

Patricia García, P. Stephen, Shreya Shah et al.

2024 · 209 Zit.

Digital twins for predictive oncology will be a paradigm shift for precision cancer care

Tina Hernandez‐Boussard, Paul Macklin, Emily J. Greenspan et al.

2021 · 207 Zit.

Developing a delivery science for artificial intelligence in healthcare

Ron Li, Steven M. Asch, Nigam H. Shah

2020 · 183 Zit.

Chatbot vs Medical Student Performance on Free-Response Clinical Reasoning Examinations

Eric Strong, Alicia DiGiammarino, Yingjie Weng et al.

2023 · 164 Zit.

Training confounder-free deep learning models for medical applications

Qingyu Zhao, Ehsan Adeli, Kilian M. Pohl

2020 · 154 Zit.