Dependence between cognitive impairment and metabolic syndrome applied to a Brazilian elderly dataset

Autor(es)

Junior Gross, Tadeu ^[1] ; Araujo, Renata Bezerra ^[2] ; Carvalho Vale, Francisco Assis ^[3] ; Bessani, Michel ^[1] ; Maciel, Carlos Dias ^[1]

Afiliação do(s) autor(es)

^[1] Univ Sao Paulo, Dept Elect & Comp Engn, Sao Carlos, SP - Brazil

^[2] Univ Fed Sao Carlos, Dept Nursing, Sao Carlos, SP - Brazil

^[3] Univ Fed Sao Carlos, Dept Med, Sao Carlos, SP - Brazil

• Tipo de documento: Artigo Científico
• Fonte: ARTIFICIAL INTELLIGENCE IN MEDICINE; v. 90, p. 53-60, AUG 2018.
• Citações Web of Science: 1

Resumo

Globally, the proportion of elderly individuals in the population has increased substantially in the last few decades. However, the risk factors that should be managed in advance to ensure a natural process of mental decline due to aging remain unknown. In this study, a dataset consisting of a Brazilian elderly sample was modelled using a Bayesian Network (BN) approach to uncover connections between cognitive performance measures and potential influence factors. Regarding its structure (a Directed Acyclic Graph), it was investigated the probabilistic dependence mechanism between two variables of medical interest: the suspected risk factor known as Metabolic Syndrome (MetS) and the indicator of mental decline referred to as Cognitive Impairment (CI). In this investigation, the concept known in the context of a BN as D-separation has been employed. Results of the conducted study revealed that the dependence between MetS and Cognitive Variables (CI and its direct determinants) in fact exists and depends on both Body Mass Index (BMI) and age. (AU)

• Processo FAPESP: 14/50851-0 - INCT 2014: Instituto Nacional de Ciência e Tecnologia para Sistemas Autônomos Cooperativos Aplicados em Segurança e Meio Ambiente
• Beneficiário: Marco Henrique Terra
• Modalidade de apoio: Auxílio à Pesquisa - Temático