University of Wisconsin–Madison
Relevante Arbeiten
Meistzitierte Publikationen im Bereich Gesundheit & MedTech
Do no harm: a roadmap for responsible machine learning for health care
Jenna Wiens, Suchi Saria, Mark Sendak et al.
2019 · 934 Zit.
Federated learning for predicting clinical outcomes in patients with COVID-19
Ittai Dayan, Holger R. Roth, Aoxiao Zhong et al.
2021 · 685 Zit.
Surgical data science for next-generation interventions
Lena Maier‐Hein, S. Swaroop Vedula, Stefanie Speidel et al.
2017 · 512 Zit.
The TRIPOD-LLM reporting guideline for studies using large language models
Jack Gallifant, Majid Afshar, Saleem Ameen et al.
2025 · 282 Zit.
Sharing ICU Patient Data Responsibly Under the Society of Critical Care Medicine/European Society of Intensive Care Medicine Joint Data Science Collaboration: The Amsterdam University Medical Centers Database (AmsterdamUMCdb) Example*
Patrick Thoral, Jan M. Peppink, Ronald H. Driessen et al.
2021 · 251 Zit.
Student privacy in learning analytics: An information ethics perspective
Alan Rubel, Kyle M. L. Jones
2016 · 230 Zit.
Human–machine teaming is key to AI adoption: clinicians’ experiences with a deployed machine learning system
Katharine E. Henry, Rachel Kornfield, Anirudh Sridharan et al.
2022 · 189 Zit.
Surveying Public Perceptions of Artificial Intelligence in Health Care in the United States: Systematic Review
Becca Beets, Todd P. Newman, Emily L. Howell et al.
2023 · 124 Zit.
The effect of using a large language model to respond to patient messages
Shan Chen, Marco Guevara-Vega, Shalini Moningi et al.
2024 · 115 Zit.
Perceptual and Interpretive Error in Diagnostic Radiology—Causes and Potential Solutions
Andrew J. Degnan, Emily H. Ghobadi, Peter Hardy et al.
2018 · 115 Zit.
Use of artificial intelligence in critical care: opportunities and obstacles
Michael R. Pinsky, Armando Bedoya, Azra Bihorac et al.
2024 · 114 Zit.
How to Create a Great Radiology Report
Michael Hartung, Ian Bickle, Frank Gaillard et al.
2020 · 110 Zit.
Nuclear Medicine and Artificial Intelligence: Best Practices for Evaluation (the RELAINCE Guidelines)
Abhinav K. Jha, Tyler Bradshaw, Irène Buvat et al.
2022 · 100 Zit.
Comparative Evaluation of LLMs in Clinical Oncology
Nicholas R. Rydzewski, Deepak Dinakaran, Shuang G. Zhao et al.
2024 · 93 Zit.
Nuclear Medicine and Artificial Intelligence: Best Practices for Algorithm Development
Tyler Bradshaw, Ronald Boellaard, Joyita Dutta et al.
2021 · 90 Zit.