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Journal of Mind and Medical Sciences is published by MDPI from Volume 12 Issue 1 (2025). Previous articles were published by another publisher in Open Access under a CC-BY (or CC-BY-NC-ND) licence, and they are hosted by MDPI on mdpi.com as a courtesy and upon agreement with Valparaiso University (ValpoScholar).
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Review

Artificial Intelligence and Liver Transplantation; Literature Review

by
Maria Serban
1,
Irina Balescu
1,
Sorin Petrea
1,2,†,
Bodan Gaspar
1,3,†,
Lucian Pop
1,4,
Valentin Varlas
1,5,
Marilena Stoian
1,6,
Camelia Diaconu
1,7,
Cristian Balalau
1,8,* and
Nicolae Bacalbasa
1,9,†
1
Faculty of General Medicine, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
2
Department of Surgery, Ion Cantacuzino Clinical Hospital, Bucharest, Romania
3
Department of Visceral Surgery, Floreasca Clinical Emergency Hospital, Bucharest, Romania
4
Department of Obstetrics and Gynecology, Alessandrescu-Rusescu National Institute of Mother and Child Care, Bucharest, Romania
5
Department of Obstetrics and Gynecology, Filantropia Clinical Hospital, Bucharest, Romania
6
Department of Internal Medicine and Nephrology, Dr. Ion Cantacuzino Hospital, Bucharest, Romania
7
Department of Internal Medicine, Floreasca Clinical Emergency Hospital, Bucharest, Romania
8
Department of General Surgery, St. Pantelimon Emergency Clinical Hospital, Bucharest, Romania
9
Department of Visceral Surgery, Fundeni Clinical Institute, Bucharest, Romania
*
Author to whom correspondence should be addressed.
†
Authors with equal contributions.
J. Mind Med. Sci. 2024, 11(2), 374-380; https://doi.org/10.22543/2392-7674.1532
Submission received: 16 April 2024 / Revised: 16 May 2024 / Accepted: 2 June 2024 / Published: 31 October 2024

Abstract

Liver transplantation is the last life-saving solution for patients with end stage liver disease. The discrepancy between waiting list and available organs has led to the appearance of extended donation criteria and the development of several scores (Child-Pugh score, MELD score, DRI score, SOFT score), in order to find the most suitable donor-recipient match. But none of these scores can predict survival after transplantation. Artificial Intelligence (AI) has recently been shown as an excellent tool for the study of the liver and comes in this aid with its various methods (random forest, artificial neural networks, decision tree, Bayesian networks, and support vector machine). Materials and Methods. By reviewing the literature (mostly retrospective multicenter studies), we aimed to establish if the AI is a proper or even a more accurate method of predicting posttransplant survival, in comparison with the existing linear statistical models. Results. Machine learning showed better results than several current scoring systems that use either isolated donor/recipient scores or combined donor/recipient factors. The advantages of this model are its capacity for analyzing both linear and nonlinear relationships between features and outcomes, its robustness of overfitting by design, and built-in insights into feature importance aiding model explainability. Nevertheless, machine learning has its limitations because it requires large amounts of data, which can be difficult to obtain, it also requires high levels of technical skill, can be difficult to engineer and it’s expensive. Conclusion. AI may have significant potential in aiding clinical decision-making during liver transplantation, including donor-recipient matching.
Keywords: liver transplantation; artificial intelligence; machine learning; decision making; survival liver transplantation; artificial intelligence; machine learning; decision making; survival

Share and Cite

MDPI and ACS Style

Serban, M.; Balescu, I.; Petrea, S.; Gaspar, B.; Pop, L.; Varlas, V.; Stoian, M.; Diaconu, C.; Balalau, C.; Bacalbasa, N. Artificial Intelligence and Liver Transplantation; Literature Review. J. Mind Med. Sci. 2024, 11, 374-380. https://doi.org/10.22543/2392-7674.1532

AMA Style

Serban M, Balescu I, Petrea S, Gaspar B, Pop L, Varlas V, Stoian M, Diaconu C, Balalau C, Bacalbasa N. Artificial Intelligence and Liver Transplantation; Literature Review. Journal of Mind and Medical Sciences. 2024; 11(2):374-380. https://doi.org/10.22543/2392-7674.1532

Chicago/Turabian Style

Serban, Maria, Irina Balescu, Sorin Petrea, Bodan Gaspar, Lucian Pop, Valentin Varlas, Marilena Stoian, Camelia Diaconu, Cristian Balalau, and Nicolae Bacalbasa. 2024. "Artificial Intelligence and Liver Transplantation; Literature Review" Journal of Mind and Medical Sciences 11, no. 2: 374-380. https://doi.org/10.22543/2392-7674.1532

APA Style

Serban, M., Balescu, I., Petrea, S., Gaspar, B., Pop, L., Varlas, V., Stoian, M., Diaconu, C., Balalau, C., & Bacalbasa, N. (2024). Artificial Intelligence and Liver Transplantation; Literature Review. Journal of Mind and Medical Sciences, 11(2), 374-380. https://doi.org/10.22543/2392-7674.1532

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