Vanderbilt University Medical Center
Relevante Arbeiten
Meistzitierte Publikationen im Bereich Gesundheit & MedTech
The Medical Segmentation Decathlon
Michela Antonelli, Annika Reinke, Spyridon Bakas et al.
2022 · 1.164 Zit.
Artificial intelligence, bias and clinical safety
Robert Challen, Joshua C. Denny, Martin Pitt et al.
2019 · 885 Zit.
Artificial Intelligence in Health Care
Michael E. Matheny, Danielle Whicher, Sonoo Thadaney Israni
2019 · 626 Zit.
Assessing the Accuracy and Reliability of AI-Generated Medical Responses: An Evaluation of the Chat-GPT Model
Douglas B. Johnson, Rachel Goodman, James R. Patrinely et al.
2023 · 586 Zit.
Utility of ChatGPT in Clinical Practice
Jialin Liu, Changyu Wang, Siru Liu
2023 · 500 Zit.
Ethical Considerations of Using ChatGPT in Health Care
Changyu Wang, Siru Liu, Hao Yang et al.
2023 · 491 Zit.
Accuracy and Reliability of Chatbot Responses to Physician Questions
Rachel Goodman, James R. Patrinely, Cosby A. Stone et al.
2023 · 428 Zit.
Using AI-generated suggestions from ChatGPT to optimize clinical decision support
Siru Liu, Aileen P. Wright, Barron L. Patterson et al.
2023 · 391 Zit.
The potential of artificial intelligence to improve patient safety: a scoping review
David W. Bates, David M. Levine, Ania Syrowatka et al.
2021 · 283 Zit.
Clinical Implications and Challenges of Artificial Intelligence and Deep Learning
William W. Stead
2018 · 253 Zit.
Assessing ChatGPT Responses to Common Patient Questions Regarding Total Hip Arthroplasty
Aleksander P. Mika, J Ryan Martin, Stephen M. Engstrom et al.
2023 · 236 Zit.
Competencies for the Use of Artificial Intelligence–Based Tools by Health Care Professionals
Regina G. Russell, Laurie L. Novak, Mehool Patel et al.
2022 · 235 Zit.
A systematic review of large language models and their implications in medical education
Harrison Lucas, Jeffrey S. Upperman, Jamie R. Robinson
2024 · 215 Zit.
Human-Centered Design to Address Biases in Artificial Intelligence
You Chen, Ellen Wright Clayton, Laurie L. Novak et al.
2023 · 177 Zit.
Improving Cancer Data Interoperability: The Promise of the Minimal Common Oncology Data Elements (mCODE) Initiative
Travis Osterman, May Terry, Robert S. Miller
2020 · 174 Zit.