Machine-learning algorithms for predicting results in liver transplantation: the problem of donor-recipient matching.

Journal: Current opinion in organ transplantation

PMID: 32487891

Abstract

PURPOSE OF REVIEW: Classifiers based on artificial intelligence can be useful to solve decision problems related to the inclusion or removal of possible liver transplant candidates, and assisting in the heterogeneous field of donor-recipient (D-R) matching.

Authors

Javier Briceño

Liver Transplantation Unit, Reina Sofía Hospital, Av. Menéndez Pidal, 14004 Córdoba, Spain.
María Dolores Ayllón

Unit of Hepatobiliary Surgery and Liver Transplantation, Córdoba, Spain.
Rubén Ciria

Liver Transplantation Unit, Reina Sofía Hospital, Av. Menéndez Pidal, 14004 Córdoba, Spain.

Keywords

Donor Selection Graft Survival Humans Liver Transplantation Machine Learning Neural Networks, Computer Prognosis Risk Factors Tissue and Organ Procurement Tissue Donors

External Resources

View on PubMed Access via DOI PubMed (32487891)

Machine-learning algorithms for predicting results in liver transplantation: the problem of donor-recipient matching.

Abstract

Authors

Keywords

External Resources

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