Utilize este identificador para referenciar este registo: https://hdl.handle.net/10316/103188
Título: The Road to Personalized Medicine in Alzheimer's Disease: The Use of Artificial Intelligence
Autor: Silva-Spínola, Anuschka
Baldeiras, Inês E. 
Arrais, Joel P. 
Santana, Isabel 
Palavras-chave: Alzheimer’s disease; artificial intelligence; AD models; machine learning; data science
Data: 29-Jan-2022
Projeto: FCT - DFA/BD/6393/2020 
CENTRO-01-0145-FEDER-000008 
info:eu-repo/grantAgreement/UIDB/04539/2020 
Título da revista, periódico, livro ou evento: Biomedicines
Volume: 10
Número: 2
Resumo: Dementia remains an extremely prevalent syndrome among older people and represents a major cause of disability and dependency. Alzheimer's disease (AD) accounts for the majority of dementia cases and stands as the most common neurodegenerative disease. Since age is the major risk factor for AD, the increase in lifespan not only represents a rise in the prevalence but also adds complexity to the diagnosis. Moreover, the lack of disease-modifying therapies highlights another constraint. A shift from a curative to a preventive approach is imminent and we are moving towards the application of personalized medicine where we can shape the best clinical intervention for an individual patient at a given point. This new step in medicine requires the most recent tools and analysis of enormous amounts of data where the application of artificial intelligence (AI) plays a critical role on the depiction of disease-patient dynamics, crucial in reaching early/optimal diagnosis, monitoring and intervention. Predictive models and algorithms are the key elements in this innovative field. In this review, we present an overview of relevant topics regarding the application of AI in AD, detailing the algorithms and their applications in the fields of drug discovery, and biomarkers.
URI: https://hdl.handle.net/10316/103188
ISSN: 2227-9059
DOI: 10.3390/biomedicines10020315
Direitos: openAccess
Aparece nas coleções:I&D CIBB - Artigos em Revistas Internacionais
I&D CISUC - Artigos em Revistas Internacionais
FMUC Medicina - Artigos em Revistas Internacionais

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