University of Virginia
Relevante Arbeiten
Meistzitierte Publikationen im Bereich Gesundheit & MedTech
Artificial intelligence for diagnosis and Gleason grading of prostate cancer: the PANDA challenge
Wouter Bulten, Kimmo Kartasalo, Po-Hsuan Cameron Chen et al.
2022 · 446 Zit.
Natural language processing of symptoms documented in free-text narratives of electronic health records: a systematic review
Theresa A. Koleck, Caitlin Dreisbach, Philip E. Bourne et al.
2018 · 410 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.
Economics of Artificial Intelligence in Healthcare: Diagnosis vs. Treatment
Narendra N. Khanna, Mahesh Maindarkar, Vijay Viswanathan et al.
2022 · 307 Zit.
ChatGPT: Applications, Opportunities, and Threats
Aram Bahrini, Mohammadsadra Khamoshifar, Hossein Abbasimehr et al.
2023 · 262 Zit.
The Janus Effect of Generative AI: Charting the Path for Responsible Conduct of Scholarly Activities in Information Systems
Anjana Susarla, Ram D. Gopal, Jason Bennett Thatcher et al.
2023 · 216 Zit.
Artificial Intelligence and the Future of Surgical Robotics
Sandip S. Panesar, Yvonne Cagle, Divya Chander et al.
2019 · 192 Zit.
The reproducibility crisis in the age of digital medicine
Aaron Stupple, David Singerman, Leo Anthony Celi
2019 · 142 Zit.
Artificial intelligence for cardiovascular disease risk assessment in personalised framework: a scoping review
Manasvi Singh, Ashish Kumar, Narendra N. Khanna et al.
2024 · 110 Zit.
Future of Artificial Intelligence—Machine Learning Trends in Pathology and Medicine
Matthew G. Hanna, Liron Pantanowitz, Rajesh Dash et al.
2025 · 106 Zit.
Advancing Human-AI Complementarity: The Impact of User Expertise and Algorithmic Tuning on Joint Decision Making
Kori Inkpen, Shreya Chappidi, Keri Mallari et al.
2023 · 92 Zit.
Introduction to Artificial Intelligence and Machine Learning for Pathology
James H. Harrison, John R. Gilbertson, Matthew G. Hanna et al.
2021 · 81 Zit.
Demographic bias in misdiagnosis by computational pathology models
Anurag Vaidya, Richard J. Chen, Drew F. K. Williamson et al.
2024 · 79 Zit.
Understanding the bias in machine learning systems for cardiovascular disease risk assessment: The first of its kind review
Jasjit S. Suri, Mrinalini Bhagawati, Sudip Paul et al.
2022 · 79 Zit.
Who Goes First? Influences of Human-AI Workflow on Decision Making in Clinical Imaging
Riccardo Fogliato, Shreya Chappidi, Matthew P. Lungren et al.
2022 · 77 Zit.