University of Michigan
Relevante Arbeiten
Meistzitierte Publikationen im Bereich Gesundheit & MedTech
Privacy in the age of medical big data
W. Nicholson Price, I. Glenn Cohen
2018 · 1.312 Zit.
Do no harm: a roadmap for responsible machine learning for health care
Jenna Wiens, Suchi Saria, Mark Sendak et al.
2019 · 916 Zit.
The Clinician and Dataset Shift in Artificial Intelligence
Samuel G. Finlayson, Adarsh Subbaswamy, Karandeep Singh et al.
2021 · 576 Zit.
Potential Liability for Physicians Using Artificial Intelligence
W. Nicholson Price, Sara Gerke, I. Glenn Cohen
2019 · 466 Zit.
Artificial intelligence for diagnosis and Gleason grading of prostate cancer: the PANDA challenge
Wouter Bulten, Kimmo Kartasalo, Po-Hsuan Cameron Chen et al.
2022 · 455 Zit.
Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI
Baptiste Vasey, Myura Nagendran, Bruce Campbell et al.
2022 · 444 Zit.
The Lancet Commission on diagnostics: transforming access to diagnostics
K A Fleming, Susan Horton, Michael L. Wilson et al.
2021 · 409 Zit.
AutoZOOM: Autoencoder-Based Zeroth Order Optimization Method for Attacking Black-Box Neural Networks
Chun‐Chen Tu, Paishun Ting, Pin‐Yu Chen et al.
2019 · 364 Zit.
Patient and general public attitudes towards clinical artificial intelligence: a mixed methods systematic review
Albert T. Young, Dominic Amara, A. Bhattacharya et al.
2021 · 330 Zit.
A scoping review of artificial intelligence in medical education: BEME Guide No. 84
Morris Gordon, Michelle Daniel, Aderonke Ajiboye et al.
2024 · 325 Zit.
Performance of GPT-3.5 and GPT-4 on the Japanese Medical Licensing Examination: Comparison Study
Soshi Takagi, Takashi Watari, Ayano Erabi et al.
2023 · 284 Zit.
Updates in Human-AI Teams: Understanding and Addressing the Performance/Compatibility Tradeoff
Gagan Bansal, Besmira Nushi, Ece Kamar et al.
2019 · 272 Zit.
Big data and black-box medical algorithms
W. Nicholson Price
2018 · 240 Zit.
Structured Reporting in Radiology
Dhakshinamoorthy Ganeshan, Phuong-Anh T. Duong, Linda Probyn et al.
2017 · 231 Zit.
PROBAST+AI: an updated quality, risk of bias, and applicability assessment tool for prediction models using regression or artificial intelligence methods
Karel G.M. Moons, Johanna AAG Damen, T. K. Kaul et al.
2025 · 221 Zit.