Carnegie Mellon University
Relevante Arbeiten
Meistzitierte Publikationen im Bereich Gesundheit & MedTech
A Survey on Evaluation of Large Language Models
Yupeng Chang, Xu Wang, Jindong Wang et al.
2024 · 2.332 Zit.
Designing Theory-Driven User-Centric Explainable AI
Danding Wang, Qian Yang, Ashraf Abdul et al.
2019 · 834 Zit.
A snapshot of the frontiers of fairness in machine learning
Alexandra Chouldechova, Aaron Roth
2020 · 338 Zit.
Algorithmic bias: Senses, sources, solutions
Sina Fazelpour, David Danks
2021 · 241 Zit.
Unremarkable AI
Qian Yang, Aaron Steinfeld, John Zimmerman
2019 · 231 Zit.
Evaluation of Machine-Learning Algorithms for Predicting Opioid Overdose Risk Among Medicare Beneficiaries With Opioid Prescriptions
Wei-Hsuan Lo-Ciganic, James L. Huang, Hao Helen Zhang et al.
2019 · 229 Zit.
“Brilliant AI Doctor” in Rural Clinics: Challenges in AI-Powered Clinical Decision Support System Deployment
Dakuo Wang, Liuping Wang, Zhan Zhang et al.
2021 · 189 Zit.
Technology readiness levels for machine learning systems
Alexander Lavin, Ciarán Lee, Alessya Visnjic et al.
2022 · 157 Zit.
The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective
Satyapriya Krishna, Tessa Han, Alex Gu et al.
2023 · 148 Zit.
In defense of the black box
Elizabeth A. Holm
2019 · 147 Zit.
A Human-AI Collaborative Approach for Clinical Decision Making on Rehabilitation Assessment
Min Hun Lee, Daniel P. Siewiorek, Asim Smailagic et al.
2021 · 126 Zit.
Improving Human-AI Partnerships in Child Welfare: Understanding Worker Practices, Challenges, and Desires for Algorithmic Decision Support
Anna Kawakami, Venkatesh Sivaraman, Hao-Fei Cheng et al.
2022 · 126 Zit.
Toward fairness in AI for people with disabilities SBG@a research roadmap
Anhong Guo, Ece Kamar, Jennifer Wortman Vaughan et al.
2020 · 123 Zit.
The Internal State of an LLM Knows When It’s Lying
Amos Azaria, Tom M. Mitchell
2023 · 121 Zit.
Ignore, Trust, or Negotiate: Understanding Clinician Acceptance of AI-Based Treatment Recommendations in Health Care
Venkatesh Sivaraman, Leigh A. Bukowski, Joel Levin et al.
2023 · 110 Zit.