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University of Florida

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Meistzitierte Publikationen im Bereich Gesundheit & MedTech

Artificial Intelligence and Surgical Decision-making

Tyler J. Loftus, Patrick Tighe, Amanda C. Filiberto et al.

2019 · 528 Zit.

Developing a model for AI Across the curriculum: Transforming the higher education landscape via innovation in AI literacy

Jane Southworth, Kati W. Migliaccio, Joe Glover et al.

2023 · 472 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 · 455 Zit.

Artificial intelligence for diagnosis and Gleason grading of prostate cancer: the PANDA challenge

van der Laak J, Corrado GS, Allan R et al.

2022 · 390 Zit.

A study of generative large language model for medical research and healthcare

Peng Cheng, Xi Yang, Aokun Chen et al.

2023 · 348 Zit.

Accessing Artificial Intelligence for Clinical Decision-Making

Chris Giordano, Meghan Brennan, Basma Mohamed et al.

2021 · 288 Zit.

Using ChatGPT to evaluate cancer myths and misconceptions: artificial intelligence and cancer information

Skyler B. Johnson, Andy J. King, Echo L. Warner et al.

2023 · 285 Zit.

Time to reality check the promises of machine learning-powered precision medicine

Jack Wilkinson, Kellyn F Arnold, Eleanor J. Murray et al.

2020 · 236 Zit.

Improved Trust in Human-Robot Collaboration With ChatGPT

Yang Ye, Hengxu You, Jing Du

2023 · 187 Zit.

A Call to Address AI “Hallucinations” and How Healthcare Professionals Can Mitigate Their Risks

Rami Hatem, Brianna Simmons, Joseph Thornton

2023 · 144 Zit.

DeepSOFA: A Continuous Acuity Score for Critically Ill Patients using Clinically Interpretable Deep Learning

Benjamin Shickel, Tyler J. Loftus, Lasith Adhikari et al.

2019 · 143 Zit.

Performance of a Machine Learning Algorithm Using Electronic Health Record Data to Predict Postoperative Complications and Report on a Mobile Platform

Yuanfang Ren, Tyler J. Loftus, Shounak Datta et al.

2022 · 117 Zit.

Generalizability of Machine Learning Models: Quantitative Evaluation of Three Methodological Pitfalls

Farhad Maleki, Katie Ovens, Rajiv Gupta et al.

2022 · 117 Zit.

Transformers and large language models in healthcare: A review

Subhash Nerella, Sabyasachi Bandyopadhyay, Jiaqing Zhang et al.

2024 · 110 Zit.

Use of artificial intelligence in critical care: opportunities and obstacles

Michael R. Pinsky, Armando Bedoya, Azra Bihorac et al.

2024 · 109 Zit.