New York University

Checklist for Artificial Intelligence in Medical Imaging (CLAIM): A Guide for Authors and Reviewers

John Mongan, Linda Moy, Charles E. Kahn

2020 · 1.148 Zit.

ChatGPT and Other Large Language Models Are Double-edged Swords

Yiqiu Shen, Laura Heacock, Jonathan Elias et al.

2023 · 964 Zit.

Federated learning for predicting clinical outcomes in patients with COVID-19

Ittai Dayan, Holger R. Roth, Aoxiao Zhong et al.

2021 · 657 Zit.

Medical 3D Printing for the Radiologist

Dimitris Mitsouras, Peter Liacouras, Amir Imanzadeh et al.

2015 · 607 Zit.

Ethical Machine Learning in Healthcare

Irene Y. Chen, Emma Pierson, Sherri Rose et al.

2021 · 428 Zit.

Health system-scale language models are all-purpose prediction engines

Lavender Yao Jiang, Xujin Chris Liu, Nima Pour Nejatian et al.

2023 · 408 Zit.

To Engage or Not to Engage with AI for Critical Judgments: How Professionals Deal with Opacity When Using AI for Medical Diagnosis

Sarah Lebovitz, Hila Lifshitz‐Assaf, Natalia Levina

2022 · 402 Zit.

The role of machine learning in clinical research: transforming the future of evidence generation

E. Hope Weissler, Tristan Naumann, Tomas Andersson et al.

2021 · 270 Zit.

Checklist for Artificial Intelligence in Medical Imaging (CLAIM): 2024 Update

Ali S. Tejani, Michail E. Klontzas, Anthony A. Gatti et al.

2024 · 245 Zit.

Assessment of Artificial Intelligence Chatbot Responses to Top Searched Queries About Cancer

Alexander Pan, David Musheyev, Daniel Bockelman et al.

2023 · 230 Zit.

Integrating artificial intelligence into the clinical practice of radiology: challenges and recommendations

Michael P. Recht, Marc Dewey, Keith Dreyer et al.

2020 · 229 Zit.

AI pitfalls and what not to do: mitigating bias in AI

Judy Wawira Gichoya, K.J. Thomas, Leo Anthony Celi et al.

2023 · 215 Zit.

Generative Artificial Intelligence to Transform Inpatient Discharge Summaries to Patient-Friendly Language and Format

Jonah Zaretsky, Jeong‐Min Kim, Samuel Baskharoun et al.

2024 · 205 Zit.

To explain or not to explain?—Artificial intelligence explainability in clinical decision support systems

Julia Amann, Dennis Vetter, Stig Nikolaj Fasmer Blomberg et al.

2022 · 191 Zit.

Putting ChatGPT’s Medical Advice to the (Turing) Test: Survey Study

Oded Nov, Nina Singh, David Mann

2023 · 172 Zit.