Google (United States)
Relevante Arbeiten
Meistzitierte Publikationen im Bereich Gesundheit & MedTech
A guide to deep learning in healthcare
Andre Esteva, Alexandre Robicquet, Bharath Ramsundar et al.
2018 · 4.234 Zit.
Machine Learning in Medicine
Alvin Rajkomar, Jay B. Dean, Isaac S. Kohane
2019 · 3.591 Zit.
Large language models encode clinical knowledge
Karan Singhal, Shekoofeh Azizi, Tao Tu et al.
2023 · 2.687 Zit.
Scalable and accurate deep learning with electronic health records
Alvin Rajkomar, Eyal Oren, Kai Chen et al.
2018 · 2.255 Zit.
Key challenges for delivering clinical impact with artificial intelligence
Christopher Kelly, Alan Karthikesalingam, Mustafa Suleyman et al.
2019 · 2.191 Zit.
Ensuring Fairness in Machine Learning to Advance Health Equity
Alvin Rajkomar, Michaela Hardt, Michael Howell et al.
2018 · 1.055 Zit.
Do no harm: a roadmap for responsible machine learning for health care
Jenna Wiens, Suchi Saria, Mark Sendak et al.
2019 · 894 Zit.
Closing the AI accountability gap
Inioluwa Deborah Raji, Andrew Smart, Rebecca N. White et al.
2020 · 824 Zit.
Protocol for development of a reporting guideline (TRIPOD-AI) and risk of bias tool (PROBAST-AI) for diagnostic and prognostic prediction model studies based on artificial intelligence
Gary S. Collins, Paula Dhiman, Constanza L. Andaur Navarro et al.
2021 · 736 Zit.
"Hello AI": Uncovering the Onboarding Needs of Medical Practitioners for Human-AI Collaborative Decision-Making
Carrie J. Cai, Samantha Winter, David F. Steiner et al.
2019 · 531 Zit.
How to Read Articles That Use Machine Learning
Yun Liu, Po-Hsuan Cameron Chen, Jonathan Krause et al.
2019 · 503 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 · 448 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 · 428 Zit.
Second opinion needed: communicating uncertainty in medical machine learning
Benjamin Kompa, Jasper Snoek, Andrew L. Beam
2021 · 397 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 · 390 Zit.