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Challenges and opportunities for digital twins in precision medicine from a complex systems perspective

dc.contributor.authorDomenico, Manlio De
dc.contributor.authorAllegri, Luca
dc.contributor.authorCaldarelli, Guido
dc.contributor.authord'Andrea, Valeria
dc.contributor.authorCamillo, Barbara Di
dc.contributor.authorRocha, Luis M.
dc.contributor.authorRozum, Jordan
dc.contributor.authorSbarbati, Riccardo
dc.contributor.authorZambelli, Francesco
dc.date.accessioned2025-01-29T17:13:18Z
dc.date.available2025-01-29T17:13:18Z
dc.date.issued2025
dc.description.abstractDigital twins (DTs) in precision medicine are increasingly viable, propelled by extensive data collection and advancements in artificial intelligence (AI), alongside traditional biomedical methodologies. We argue that including mechanistic simulations that produce behavior based on explicitly defined biological hypotheses and multiscale mechanisms is beneficial. It enables the exploration of diverse therapeutic strategies and supports dynamic clinical decision-making through insights from network science, quantitative biology, and digital medicine.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1038/s41746-024-01402-3pt_PT
dc.identifier.eid85218348159
dc.identifier.issn2398-6352
dc.identifier.pmcPMC11742446
dc.identifier.pmid39825012
dc.identifier.urihttp://hdl.handle.net/10400.14/47980
dc.identifier.wos001397997700001
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.titleChallenges and opportunities for digital twins in precision medicine from a complex systems perspectivept_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.titlenpj Digital Medicinept_PT
oaire.citation.volume8pt_PT
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT

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