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Artificial intelligence (AI) in rare diseases: is the future brighter?

2019-12Journal article Open access
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dc.contributor.authorBrasil, Sandra
dc.contributor.authorPascoal, Carlota
dc.contributor.authorFrancisco, Rita
dc.contributor.authorFerreira, Vanessa dos Reis
dc.contributor.authorVideira, P A
dc.contributor.authorValadão Matias, Gonçalo
dc.date.accessioned2020-04-07T14:56:19Z
dc.date.available2020-04-07T14:56:19Z
dc.date.issued2019-12
dc.description.abstractThe amount of data collected and managed in (bio)medicine is ever-increasing. Thus, there is a need to rapidly and efficiently collect, analyze, and characterize all this information. Artificial intelligence (AI), with an emphasis on deep learning, holds great promise in this area and is already being successfully applied to basic research, diagnosis, drug discovery, and clinical trials. Rare diseases (RDs), which are severely underrepresented in basic and clinical research, can particularly benefit from AI technologies. Of the more than 7000 RDs described worldwide, only 5% have a treatment. The ability of AI technologies to integrate and analyze data from different sources (e.g., multi-omics, patient registries, and so on) can be used to overcome RDs' challenges (e.g., low diagnostic rates, reduced number of patients, geographical dispersion, and so on). Ultimately, RDs' AI-mediated knowledge could significantly boost therapy development. Presently, there are AI approaches being used in RDs and this review aims to collect and summarize these advances. A section dedicated to congenital disorders of glycosylation (CDG), a particular group of orphan RDs that can serve as a potential study model for other common diseases and RDs, has also been included.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationBRASIL, Sandra; [et al] – Artificial intelligence (AI) in rare diseases: is the future brighter? Genes. ISSN 2073-4425. Vol. 10, N.º 12 (2019), pp. 1-24pt_PT
dc.identifier.doi10.3390/genes10120978pt_PT
dc.identifier.issn2073-4425
dc.identifier.urihttp://hdl.handle.net/10400.21/11426
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherMDPIpt_PT
dc.relationSFRH/BD/138647/2018 - FCTpt_PT
dc.relationSFRH/BD/124326/2016 - FCTpt_PT
dc.subjectArtificial intelligencept_PT
dc.subjectBig datapt_PT
dc.subjectCongenital disorders of glycosylationpt_PT
dc.subjectDiagnosispt_PT
dc.subjectDrug repurposingpt_PT
dc.subjectMachine learningpt_PT
dc.subjectPersonalized medicinept_PT
dc.subjectRare diseasespt_PT
dc.titleArtificial intelligence (AI) in rare diseases: is the future brighter?pt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage24pt_PT
oaire.citation.issue12pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.titleGenespt_PT
oaire.citation.volume10pt_PT
person.familyNameArduim Brasil
person.familyNamePascoal
person.familyNameBatista Francisco
person.familyNameVideira
person.familyNameValadão Matias
person.givenNameSandra Dolores
person.givenNameCarlota
person.givenNameRita Alexandra
person.givenNamePaula
person.givenNameGonçalo
person.identifier.ciencia-idB616-6C8F-F9BC
person.identifier.ciencia-idBB17-EB13-816D
person.identifier.ciencia-id6114-753E-7789
person.identifier.ciencia-id591D-F82C-45C2
person.identifier.ciencia-id361E-C437-12DC
person.identifier.orcid0000-0003-3977-7872
person.identifier.orcid0000-0001-5049-0579
person.identifier.orcid0000-0002-4398-3401
person.identifier.orcid0000-0001-5987-2485
person.identifier.orcid0000-0001-5343-9269
person.identifier.scopus-author-id6507125652
person.identifier.scopus-author-id8865647400
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication9ab80111-a1be-4b2c-ae58-32c0a4f9f1e3
relation.isAuthorOfPublicationabbebba5-ea3d-437c-b2b9-5f6bac634ebd
relation.isAuthorOfPublication021d8c7c-a6ce-46dd-b3ed-55b33f93e981
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relation.isAuthorOfPublication.latestForDiscovery55d66595-59e9-4dd0-8e93-d1dab019fea5

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