AI Innovations in Liver Transplantation: From Big Data to Better Outcomes

Artificial intelligence (AI) has emerged as a transformative field in computational research with diverse applications in medicine, particularly in the field of liver transplantation (LT) given its ability to analyze and build upon complex and multidimensional data. This literature review investigates the application of AI in LT, focusing on its role in pre-implantation biopsy evaluation, development of recipient prognosis algorithms, imaging analysis, and decision-making support systems, with the findings revealing that AI can be applied across a variety of fields within LT, including diagnosis, organ allocation, and surgery planning. As a result, algorithms are being developed to assess steatosis in pre-implantation biopsies and predict liver graft function, with AI applications displaying great accuracy across various studies included in this review. Despite its relatively recent introduction to transplantation, AI demonstrates potential in delivering cost and time-efficient outcomes. However, these tools cannot replace the role of healthcare professionals, with their widespread adoption demanding thorough clinical testing and oversight.

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Publication Details

Journal
Livers
Published
2025-03-14
DOI
https://doi.org/10.3390/livers5010014
Citations
7
Primary Topic
Liver Disease Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
9.48
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article

AI Innovations in Liver Transplantation: From Big Data to Better Outcomes

Athanasios Kofinas, Stella Vasileiadou, Georgios Katsanos, Georgios Tsoulfas et al.
7 citations
Livers
Liver Disease Diagnosis and Treatment
9.48
article

AI Innovations in Liver Transplantation: From Big Data to Better Outcomes

Athanasios Kofinas, Stella Vasileiadou, Georgios Katsanos, Georgios Tsoulfas, Konstantina-Eleni Karakasi, Eleni Avramidou, Nikolaos Antoniadis, Dominik Todorov
article en
7 citations

Abstract

Artificial intelligence (AI) has emerged as a transformative field in computational research with diverse applications in medicine, particularly in the field of liver transplantation (LT) given its ability to analyze and build upon complex and multidimensional data. This literature review investigates the application of AI in LT, focusing on its role in pre-implantation biopsy evaluation, development of recipient prognosis algorithms, imaging analysis, and decision-making support systems, with the findings revealing that AI can be applied across a variety of fields within LT, including diagnosis, organ allocation, and surgery planning. As a result, algorithms are being developed to assess steatosis in pre-implantation biopsies and predict liver graft function, with AI applications displaying great accuracy across various studies included in this review. Despite its relatively recent introduction to transplantation, AI demonstrates potential in delivering cost and time-efficient outcomes. However, these tools cannot replace the role of healthcare professionals, with their widespread adoption demanding thorough clinical testing and oversight.

LiversVol. 5(1)
Aristotle University of Thessaloniki (GR), Imperial College London (GB)
Openalex Percentile: Top 2%
Liver Disease Diagnosis and Treatment
9.48
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