Machine learning and artificial intelligence research for patient benefit: 20 critical questions on transparency, replicability, ethics, and effectiveness
Turing Institute · University of Warwick · +14 more institutions
Abstract
Machine learning, artificial intelligence, and other modern statistical methods are providing new opportunities to operationalise previously untapped and rapidly growing sources of data for patient benefit. Despite much promising research currently being undertaken, particularly in imaging, the literature as a whole lacks transparency, clear reporting to facilitate replicability, exploration for potential ethical concerns, and clear demonstrations of effectiveness. Among the many reasons why these problems exist, one of the most important (for which we provide a preliminary solution here) is the current lack of best practice guidance specific to machine learning and artificial intelligence. However, we believe…
Citation impact
- FWCI
- 17.37
- Percentile
- 100%
- References
- 73
Authors
18- SJSebastian J. VollmerCorresponding
Turing Institute, University of Warwick
- BABilal A. Mateen
Turing Institute, University of Warwick, King's College Hospital
- GBGergő Bohner
Turing Institute, University of Warwick
- FJFranz J. Király
Turing Institute, University College London
- RGRayid Ghani
University of Illinois Chicago, University of Chicago
Topics & keywords
- Transparency (behavior)
- Artificial intelligence
- Computer science
- Research ethics
- Ethical issues
- Engineering ethics
- Knowledge management
- Management science