Artificial intelligence, machine learning, and deep learning in liver transplantation
University Health Network · University of Toronto · +4 more institutions
Abstract
Liver transplantation (LT) is a life-saving treatment for individuals with end-stage liver disease. The management of LT recipients is complex, predominantly because of the need to consider demographic, clinical, laboratory, pathology, imaging, and omics data in the development of an appropriate treatment plan. Current methods to collate clinical information are susceptible to some degree of subjectivity; thus, clinical decision-making in LT could benefit from the data-driven approach offered by artificial intelligence (AI). Machine learning and deep learning could be applied in both the pre- and post-LT settings. Some examples of AI applications pre-transplant include optimising transplant candidacy…
Citation impact
- FWCI
- 61.40
- Percentile
- 100%
- References
- 89
Authors
4- MBMamatha BhatCorresponding
University Health Network, University of Toronto, Toronto Rehabilitation Institute, Toronto General Hospital
- MRMadhumitha Rabindranath
University Health Network, University of Toronto, Toronto General Hospital
- BSBeatriz Sordi Chara
Mayo Clinic, WinnMed
- DADouglas A. Simonetto
Mayo Clinic, WinnMed
Topics & keywords
- Artificial intelligence
- Context (archaeology)
- Medicine
- Machine learning
- Candidacy
- Transplantation
- Liver transplantation
- Intensive care medicine