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Influence of habits and comorbidities on liver disease

2026Conference paper Restricted access
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datacite.subject.fosCiências Médicas::Biotecnologia Médica
datacite.subject.fosCiências Médicas::Ciências da Saúde
datacite.subject.fosEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
datacite.subject.sdg04:Educação de Qualidade
datacite.subject.sdg03:Saúde de Qualidade
datacite.subject.sdg09:Indústria, Inovação e Infraestruturas
dc.contributor.authorLeite, Gabriel A.
dc.contributor.authorAzevedo, Beatriz Flamia
dc.contributor.authorPacheco, Maria F.
dc.contributor.authorFernandes, Florbela P.
dc.contributor.authorPereira, Ana I.
dc.date.accessioned2025-12-04T15:57:37Z
dc.date.available2025-12-04T15:57:37Z
dc.date.issued2026
dc.description.abstractThe prevalence of hepatocellular carcinoma is expected to continue increasing worldwide, and its difficulty in early detection highlights the need for advanced monitoring technologies. As the disease progresses, it has a serious impact on patients’ health, and in severe cases, liver transplantation becomes the only viable solution, reinforcing its importance as a global health problem. This study proposes the use of different artificial intelligence methods to compare and understand them related to liver disease. Well-known algorithms such as Random Forest and Multi-Layer Perceptron were tested, as well as ensemble methods that exploit different modeling structures. The results showed that AdaBoost, Random Forest, and Gradient Boosting performed best with Area Under the Curve of 0.89, 0.86, and 0.84 respectively. To analyze their influence on clinical results, the best-performing model was reapplied only to the non-biochemical features that compose the dataset. The results indicate that portal vein thrombosis, diabetes, and hypertension are the most influential variables, with contributions of 29.48%, 20.50%, and 16.60%, respectively.eng
dc.description.sponsorshipThis work has been supported by FCT Fundação para a Ciência e Tecnologia within the R&D Units Project Scope UIDB/00319/2020, UIDB/05757/2020 (DOI:10.54499/UIDB/05757/2020), UIDP/05757/2020 (DOI: 10.54499/UIDP/05757/2020), Erasmus Plus KA2 within the project 2021-1-PT01-KA220-HED-000023288, and HORIZON-WIDERA-2021-ACCESS-03-01 STEP - STEM Research and Equality, Diversity and Inclusion Project, under Grant Agreement No. 101078933.
dc.identifier.citationLeite, Gabriel A.; Azevedo, Beatriz Flamia; Pacheco, Maria F.; Fernandes, Florbela P.; Pereira, Ana I. (2026). Influence of Habits and Comorbidities on Liver Disease. In 5th International Conference OL2A. Cham: Springer Nature. p. 187–200. ISBN 9783032001368
dc.identifier.doi10.1007/978-3-032-00137-5_13
dc.identifier.isbn9783032001368
dc.identifier.isbn9783032001375
dc.identifier.issn1865-0929
dc.identifier.issn1865-0937
dc.identifier.urihttp://hdl.handle.net/10198/35174
dc.language.isoeng
dc.peerreviewedyes
dc.publisherSpringer Nature
dc.relationALGORITMI Research Center
dc.relationResearch Centre in Digitalization and Intelligent Robotics
dc.relationResearch Centre in Digitalization and Intelligent Robotics
dc.relation.ispartofCommunications in Computer and Information Science
dc.relation.ispartofOptimization, Learning Algorithms and Applications
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectHepatocellular carcinoma
dc.subjectMachine learning
dc.subjectHealth diagnosis
dc.subjectCancer
dc.subjectEnsemble methods
dc.subjectFeature selection
dc.titleInfluence of habits and comorbidities on liver diseaseeng
dc.typeconference paper
dspace.entity.typePublication
oaire.awardTitleALGORITMI Research Center
oaire.awardTitleResearch Centre in Digitalization and Intelligent Robotics
oaire.awardTitleResearch Centre in Digitalization and Intelligent Robotics
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00319%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F05757%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F05757%2F2020/PT
oaire.citation.endPage200
oaire.citation.startPage187
oaire.citation.title5th International Conference OL2A
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameLeite
person.familyNameAzevedo
person.familyNamePacheco
person.familyNameFernandes
person.familyNamePereira
person.givenNameGabriel A.
person.givenNameBeatriz Flamia
person.givenNameMaria F.
person.givenNameFlorbela P.
person.givenNameAna I.
person.identifier.ciencia-id8A1D-BE60-F58E
person.identifier.ciencia-id181E-855C-E62C
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person.identifier.ciencia-id501D-6FD0-CC53
person.identifier.ciencia-id0716-B7C2-93E4
person.identifier.orcid0009-0008-3273-0450
person.identifier.orcid0000-0002-8527-7409
person.identifier.orcid0000-0001-7915-0391
person.identifier.orcid0000-0001-9542-4460
person.identifier.orcid0000-0003-3803-2043
person.identifier.ridF-3168-2010
person.identifier.scopus-author-id36802474600
person.identifier.scopus-author-id35179471000
person.identifier.scopus-author-id15071961600
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
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