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Revolutionizing Kidney Transplantation

Bibliographic Details
Main Author: Ramalhete, Luís
Publication Date: 2024
Other Authors: Almeida, Paula, Ferreira, Raquel, Abade, Olga, Teixeira, Cristiana, Araújo, Rúben
Format: Other
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10362/166077
Summary: Publisher Copyright: © 2024 by the authors.
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spelling Revolutionizing Kidney TransplantationConnecting Machine Learning and Artificial Intelligence with Next-Generation Healthcare—From Algorithms to Allograftsartificial intelligencekidney transplantationmachine learningprecision medicineComputer Science (miscellaneous)Medicine (miscellaneous)Health InformaticsHealth Professions (miscellaneous)Publisher Copyright: © 2024 by the authors.This review explores the integration of artificial intelligence (AI) and machine learning (ML) into kidney transplantation (KT), set against the backdrop of a significant donor organ shortage and the evolution of ‘Next-Generation Healthcare’. Its purpose is to evaluate how AI and ML can enhance the transplantation process, from donor selection to postoperative patient care. Our methodology involved a comprehensive review of current research, focusing on the application of AI and ML in various stages of KT. This included an analysis of donor–recipient matching, predictive modeling, and the improvement in postoperative care. The results indicated that AI and ML significantly improve the efficiency and success rates of KT. They aid in better donor–recipient matching, reduce organ rejection, and enhance postoperative monitoring and patient care. Predictive modeling, based on extensive data analysis, has been particularly effective in identifying suitable organ matches and anticipating postoperative complications. In conclusion, this review discusses the transformative impact of AI and ML in KT, offering more precise, personalized, and effective healthcare solutions. Their integration into this field addresses critical issues like organ shortages and post-transplant complications. However, the successful application of these technologies requires careful consideration of their ethical, privacy, and training aspects in healthcare settings.NOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM)iNOVA4Health - pólo NMSComprehensive Health Research Centre (CHRC) - pólo NMSRUNRamalhete, LuísAlmeida, PaulaFerreira, RaquelAbade, OlgaTeixeira, CristianaAraújo, Rúben2024-04-11T00:36:01Z2024-032024-03-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/other17application/pdfhttp://hdl.handle.net/10362/166077eng2673-7426PURE: 87106648https://doi.org/10.3390/biomedinformatics4010037info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-22T18:20:23Zoai:run.unl.pt:10362/166077Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:51:04.589471Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Revolutionizing Kidney Transplantation
Connecting Machine Learning and Artificial Intelligence with Next-Generation Healthcare—From Algorithms to Allografts
title Revolutionizing Kidney Transplantation
spellingShingle Revolutionizing Kidney Transplantation
Ramalhete, Luís
artificial intelligence
kidney transplantation
machine learning
precision medicine
Computer Science (miscellaneous)
Medicine (miscellaneous)
Health Informatics
Health Professions (miscellaneous)
title_short Revolutionizing Kidney Transplantation
title_full Revolutionizing Kidney Transplantation
title_fullStr Revolutionizing Kidney Transplantation
title_full_unstemmed Revolutionizing Kidney Transplantation
title_sort Revolutionizing Kidney Transplantation
author Ramalhete, Luís
author_facet Ramalhete, Luís
Almeida, Paula
Ferreira, Raquel
Abade, Olga
Teixeira, Cristiana
Araújo, Rúben
author_role author
author2 Almeida, Paula
Ferreira, Raquel
Abade, Olga
Teixeira, Cristiana
Araújo, Rúben
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv NOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM)
iNOVA4Health - pólo NMS
Comprehensive Health Research Centre (CHRC) - pólo NMS
RUN
dc.contributor.author.fl_str_mv Ramalhete, Luís
Almeida, Paula
Ferreira, Raquel
Abade, Olga
Teixeira, Cristiana
Araújo, Rúben
dc.subject.por.fl_str_mv artificial intelligence
kidney transplantation
machine learning
precision medicine
Computer Science (miscellaneous)
Medicine (miscellaneous)
Health Informatics
Health Professions (miscellaneous)
topic artificial intelligence
kidney transplantation
machine learning
precision medicine
Computer Science (miscellaneous)
Medicine (miscellaneous)
Health Informatics
Health Professions (miscellaneous)
description Publisher Copyright: © 2024 by the authors.
publishDate 2024
dc.date.none.fl_str_mv 2024-04-11T00:36:01Z
2024-03
2024-03-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/other
format other
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/166077
url http://hdl.handle.net/10362/166077
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2673-7426
PURE: 87106648
https://doi.org/10.3390/biomedinformatics4010037
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 17
application/pdf
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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