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Advisor(s)
Abstract(s)
Hybrid models to detect dementia based on Machine Learning can provide accurate
diagnoses in individuals with neurological disorders and cognitive complications caused by Human
Immunodeficiency Virus (HIV) infection. This study proposes a hybrid approach, using Machine
Learning algorithms associated with the multicriteria method of Verbal Decision Analysis (VDA).
Dementia, which affects many HIV-infected individuals, refers to neurodevelopmental and mental
disorders. Some manuals standardize the information used in the correct detection of neurological
disorders with cognitive complications. Among the most common manuals used are the DSM-5
(Diagnostic and Statistical Manual of Mental Disorders, 5th edition) of the American Psychiatric
Association and the International Classification of Diseases, 10th edition (ICD-10)—both published
byWorld Health Organization (WHO). The model is designed to explore the predictive of specific
data. Furthermore, a well-defined database data set improves and optimizes the diagnostic models
sought in the research.
Description
Keywords
Cognitive dementia HIV Machine learning Verbal decision analysis Multicriteria model Medical diagnostic optimization
Citation
Pinheiro, L.I.C.C.; Pereira, M.L.D.; Andrade, E.C.d.; Nunes, L.C.; Abreu,W.C.d.; Pinheiro, P.G.C.D.; Holanda Filho, R.; Pinheiro, P.R. An Intelligent Multicriteria Model for Diagnosing Dementia in People Infected with Human Immunodeficiency Virus. Appl. Sci.2021, 11, 10457.
Publisher
MDPI