University of San Francisco
Relevante Arbeiten
Meistzitierte Publikationen im Bereich Gesundheit & MedTech
Scalable and accurate deep learning with electronic health records
Alvin Rajkomar, Eyal Oren, Kai Chen et al.
2018 · 2.256 Zit.
Big Data in Science and Healthcare: A Review of Recent Literature and Perspectives
Talya Miron‐Shatz, Annie Lau, Chris Paton et al.
2014 · 125 Zit.
Consensus Guidelines for Digital Scholarship in Academic Promotion
Abbas Husain, Zachary Repanshek, Manpreet Singh et al.
2020 · 67 Zit.
Current Use And Evaluation Of Artificial Intelligence And Predictive Models In US Hospitals
Paige Nong, Julia Adler‐Milstein, Nate C. Apathy et al.
2025 · 53 Zit.
The landscape of urological retractions: the prevalence of reported research misconduct
Jorge Mena, Médina Ndoye, Andrew J. Cohen et al.
2019 · 31 Zit.
<scp>ChatGPT</scp>, et al … Artificial Intelligence, Authorship, and Medical Publishing
Daniel H. Solomon, Kelli D. Allen, Patricia Katz et al.
2023 · 18 Zit.
WHO’s arrived in 2016! An updated weather forecast for integrated brain tumor diagnosis
Arie Perry
2016 · 13 Zit.
A scientometric analysis of fairness in health AI literature
Isabelle Rose I. Alberto, Nicole Rose I. Alberto, Yüksel Altınel et al.
2024 · 9 Zit.
The evaluation illusion of large language models in medicine
Monica Agrawal, Irene Y. Chen, Freya Gulamali et al.
2025 · 8 Zit.
Closing the Gap Between Machine Learning and Clinical Cancer Care—First Steps Into a Larger World
John Kang, Olivier Morin, Julian C. Hong
2020 · 7 Zit.
Who does the fairness in health AI community represent?
Isabelle Rose I. Alberto, Nicole Rose I. Alberto, Yüksel Altınel et al.
2023 · 4 Zit.
The Intersection of Radiology With Blockchain and Smart Contracts: A Perspective
Nima S. Ghorashi, Murwarit Rahimi, Reza Sirous et al.
2023 · 4 Zit.
Opening a conversation on responsible environmental data science in the age of large language models
Ruth Y. Oliver, Melissa Chapman, Nathan Emery et al.
2024 · 4 Zit.
Towards responsible artificial intelligence in healthcare—getting real about real-world data and evidence
Eileen Koski, Amar K. Das, Pei-Yun Hsueh et al.
2025 · 3 Zit.
Expert-augmented machine learning
Efstathios D. Gennatas, Jerome H. Friedman, Lyle Ungar et al.
2020 · 2 Zit.