Benjamin S. Glicksberg

Artificial Intelligence in Cardiology

2018 · 1.137 Zit. · Journal of the American College of Cardiology

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

2021 · 694 Zit. · Nature Medicine

Comparing ChatGPT and GPT-4 performance in USMLE soft skill assessments

2023 · 317 Zit. · Scientific Reports

Assessment of a Deep Learning Model Based on Electronic Health Record Data to Forecast Clinical Outcomes in Patients With Rheumatoid Arthritis

2019 · 223 Zit. · JAMA Network Open

Evaluating the use of large language model in identifying top research questions in gastroenterology

2023 · 121 Zit. · Scientific Reports

Large Language Models Are Poor Medical Coders — Benchmarking of Medical Code Querying

2024 · 116 Zit. · NEJM AI

Large language models for generating medical examinations: systematic review

2024 · 103 Zit. · BMC Medical Education

Evaluating the Utility of a Large Language Model in Answering Common Patients’ Gastrointestinal Health-Related Questions: Are We There Yet?

2023 · 97 Zit. · Diagnostics

Artificial intelligence-enabled decision support in nephrology

2022 · 91 Zit. · Nature Reviews Nephrology

Evaluating the accuracy of a state-of-the-art large language model for prediction of admissions from the emergency room

2024 · 78 Zit. · Journal of the American Medical Informatics Association

Assessing GPT-4 multimodal performance in radiological image analysis

2024 · 70 Zit. · European Radiology

Federated Learning for Healthcare Informatics

2019 · 66 Zit. · arXiv (Cornell University)

Benefits, limits, and risks of ChatGPT in medicine

2025 · 52 Zit. · Frontiers in Artificial Intelligence

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

2021 · 44 Zit. · Research Square

Implications of the Use of Artificial Intelligence Predictive Models in Health Care Settings

2023 · 41 Zit. · Annals of Internal Medicine