Schwartz/Reisman Emergency Medicine Institute

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

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

2021 · 657 Zit.

Managing extreme AI risks amid rapid progress

Yoshua Bengio, Geoffrey E. Hinton, Andrew Chi-Chih Yao et al.

2024 · 221 Zit.

Believing in black boxes: machine learning for healthcare does not need explainability to be evidence-based

Liam G. McCoy, Connor T. A. Brenna, Stacy S. Chen et al.

2021 · 109 Zit.

Federated Learning used for predicting outcomes in SARS-COV-2 patients

Mona G. Flores, Ittai Dayan, Holger R. Roth et al.

2021 · 44 Zit.

Finding Consensus on Trust in AI in Health Care: Recommendations From a Panel of International Experts

Georg Starke, Felix Gille, Alberto Termine et al.

2025 · 24 Zit.

Payments to Health Care Professionals and Teaching Hospitals by AI- and Machine Learning–Enabled Medical Device Manufacturers

David‐Dan Nguyen, Anju Murayama, Tiange Li et al.

2025 · 1 Zit.

Teaching old tools new tricks—preparing emergency medicine for the impact of machine learning-based risk prediction models

Vinyas Harish, Keerat Grewal, Muhammad Mamdani et al.

2023 · 1 Zit.