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A comparative analysis of MATLAB and Python neural networks for diabetes prediction

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dc.contributor.authorPimentel, Gabriel
dc.contributor.authorDessanti, Augusto
dc.contributor.authorTeixeira, João Paulo
dc.date.accessioned2026-05-18T15:11:42Z
dc.date.available2026-05-18T15:11:42Z
dc.date.issued2024
dc.description.abstractIn recent years, artificial intelligence (AI) has become an integral part of many everyday applications. The growth of AI is bringing intellectual benefits to humans. It is revolutionizing discovery, learning, communication, and work. Machine learning, especially deep learning, is critical to this progress, providing complex models to process data more effectively. Neural networks, which emulate biological processes, find applications across diverse fields, notably in medicine, where they automate disease diagnosis and prediction tasks, such as diabetes. This paper proposes a comparative analysis between Python and MATLAB for diabetes prediction using a dataset with 100,000 individuals. The study conducts simulations on both platforms and validates the results using metrics such as precision, specificity, accuracy and F-measure. Additionally, the study emphasizes the importance of platform selection based on considerations of functionality and cost, offering insights into optimizing outcomes in healthcare applications.por
dc.description.sponsorshipThe authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for financial support through national funds FCT/MCTES (PIDDAC) to CeDRI, UIDB/05757/2020 (DOI: 10.54499 UIDB/05757/2020)and UIDP/05757/2020 (DOI: 10.54499/UIDB/05757/2020) and SusTEC, LA/P/0007/2020 (DOI: 10.54499/LA/P/0007/2020).
dc.identifier.citationPimentel, Gabriel; Dessanti, Augusto; Teixeira, João Paulo (2024). A comparative analysis of MATLAB and Python neural networks for diabetes prediction. 4th International Conference on Optimization, Learning Algorithms and Applications, OL2A 2024. 2280, p. 205-220. ISBN 9783031774263
dc.identifier.doi10.1007/978-3-031-77426-3_14
dc.identifier.isbn9783031774263
dc.identifier.urihttp://hdl.handle.net/10198/36713
dc.language.isoeng
dc.peerreviewedyes
dc.publisherSpringer Nature Switzerland
dc.relationResearch Centre in Digitalization and Intelligent Robotics
dc.relationAssociate Laboratory for Sustainability and Tecnology in Mountain Regions - LA/P/0007/2020
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.titleA comparative analysis of MATLAB and Python neural networks for diabetes predictionpor
dc.typeconference object
dspace.entity.typePublication
oaire.awardNumberUIDB/05757/2020
oaire.awardNumberLA/P/0007/2020
oaire.awardTitleResearch Centre in Digitalization and Intelligent Robotics
oaire.awardTitleAssociate Laboratory for Sustainability and Tecnology in Mountain Regions - LA/P/0007/2020
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F05757%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/LA%2FP%2F0007%2F2020/PT
oaire.citation.endPage220
oaire.citation.startPage205
oaire.citation.title4th International Conference on Optimization, Learning Algorithms and Applications, OL2A 2024
oaire.citation.volume2280
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameTeixeira
person.givenNameJoão Paulo
person.identifier663194
person.identifier.ciencia-id4F15-B322-59B4
person.identifier.orcid0000-0002-6679-5702
person.identifier.ridN-6576-2013
person.identifier.scopus-author-id57069567500
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
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