Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/89510
Registo completo
Campo DC | Valor | Idioma |
---|---|---|
dc.contributor.author | Vieira, Ana | por |
dc.contributor.author | Carneiro, Maria | por |
dc.contributor.author | Novais, Paulo | por |
dc.contributor.author | Corchado, Juan | por |
dc.contributor.author | Marreiros, Goreti | por |
dc.date.accessioned | 2024-03-14T09:16:49Z | - |
dc.date.issued | 2023 | - |
dc.identifier.issn | 1088-467X | - |
dc.identifier.uri | https://hdl.handle.net/1822/89510 | - |
dc.description.abstract | A large percentage of the worldwide population is affected by chronic diseases, leading to a burden of the patient and the national healthcare systems. Recommendation systems are used for the personalization of healthcare due to their capacity of performing predictive analyses based on the patient's clinical data. This systematic literature review presents four research questions to provide an overall state of the art of the use of recommendation systems applied to the healthcare of patients with chronic diseases. Disease management was identified as the main purpose of the systems proposed in the literature. However, few solutions provide support to physicians in the clinical decision-making. Ontologies and rule-based systems were the artificial intelligence techniques most used in the systems since they can easily implement clinical guidelines. Current challenges of these systems include the low adherence, data sparsity, heterogeneous data, and explainability, that affect the success of the recommendation system. The results also show that there are few systems that provide support to patients with multiple chronic conditions. The findings of this literature review should be considered in the development of future recommendation systems that aim to support the management of chronic diseases. | por |
dc.description.sponsorship | This research work was developed under the projects Inno4Health (EUREKA-ITEA3: 19008; POCI-01-0247-FEDER-069523), PHE (EUREKA-ITEA3: 16040), AIRDOC (NORTE-01-0247-FEDER-033275) and by National Funds through FCT (Fundação para a Ciência e a Tecnologia) under UIDB/00760/2020. Ana Vieira is supported by national funds through FCT PhD studentship with reference UI/BD/151115/202 | por |
dc.language.iso | eng | por |
dc.publisher | IOS Press | por |
dc.relation | NORTE-01-0247-FEDER-033275 | por |
dc.relation | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00760%2F2020/PT | por |
dc.relation | info:eu-repo/grantAgreement/FCT/OE/UI%2FBD%2F151115%2F2021/PT | por |
dc.relation | POCI-01-0247-FEDER-069523 | por |
dc.rights | restrictedAccess | por |
dc.subject | Chronic diseases | por |
dc.subject | eHealth | por |
dc.subject | Healthcare | por |
dc.subject | Recommendation systems | por |
dc.subject | Systematic literature review | por |
dc.title | A systematic review on recommendation systems applied to chronic diseases | por |
dc.type | article | por |
dc.peerreviewed | yes | por |
dc.relation.publisherversion | https://content.iospress.com/articles/intelligent-data-analysis/ida220394 | por |
oaire.citationStartPage | 1223 | por |
oaire.citationEndPage | 1265 | por |
oaire.citationIssue | 5 | por |
oaire.citationVolume | 27 | por |
dc.date.updated | 2024-03-13T16:30:23Z | - |
dc.identifier.eissn | 1571-4128 | - |
dc.identifier.doi | 10.3233/IDA-220394 | por |
dc.date.embargo | 10000-01-01 | - |
sdum.export.identifier | 13381 | - |
sdum.journal | Intelligent Data Analysis | por |
Aparece nas coleções: | CAlg - Artigos em revistas internacionais / Papers in international journals |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
---|---|---|---|---|
Manuscript T22-394-6943.pdf Acesso restrito! | 737,96 kB | Adobe PDF | Ver/Abrir |