An Intelligent Multicriteria Model for Diagnosing Dementia in People Infected with Human Immunodeficiency Virus
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...
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2021
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oai:doaj.org-article:108fe08dc31341938bae07e846f3500d2021-11-11T15:24:35ZAn Intelligent Multicriteria Model for Diagnosing Dementia in People Infected with Human Immunodeficiency Virus10.3390/app1121104572076-3417https://doaj.org/article/108fe08dc31341938bae07e846f3500d2021-11-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/21/10457https://doaj.org/toc/2076-3417Hybrid 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 by World 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.Luana I. C. C. PinheiroMaria Lúcia D. PereiraEvandro C. de AndradeLuciano C. NunesWilson C. de AbreuPedro Gabriel Calíope D. PinheiroRaimir Holanda FilhoPlácido Rogerio PinheiroMDPI AGarticlecognitive dementiaHIVmachine learningverbal decision analysismulticriteria modelmedical diagnostic optimizationTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 10457, p 10457 (2021) |
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cognitive dementia HIV machine learning verbal decision analysis multicriteria model medical diagnostic optimization Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 |
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cognitive dementia HIV machine learning verbal decision analysis multicriteria model medical diagnostic optimization Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Luana I. C. C. Pinheiro Maria Lúcia D. Pereira Evandro C. de Andrade Luciano C. Nunes Wilson C. de Abreu Pedro Gabriel Calíope D. Pinheiro Raimir Holanda Filho Plácido Rogerio Pinheiro An Intelligent Multicriteria Model for Diagnosing Dementia in People Infected with Human Immunodeficiency Virus |
description |
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 by World 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. |
format |
article |
author |
Luana I. C. C. Pinheiro Maria Lúcia D. Pereira Evandro C. de Andrade Luciano C. Nunes Wilson C. de Abreu Pedro Gabriel Calíope D. Pinheiro Raimir Holanda Filho Plácido Rogerio Pinheiro |
author_facet |
Luana I. C. C. Pinheiro Maria Lúcia D. Pereira Evandro C. de Andrade Luciano C. Nunes Wilson C. de Abreu Pedro Gabriel Calíope D. Pinheiro Raimir Holanda Filho Plácido Rogerio Pinheiro |
author_sort |
Luana I. C. C. Pinheiro |
title |
An Intelligent Multicriteria Model for Diagnosing Dementia in People Infected with Human Immunodeficiency Virus |
title_short |
An Intelligent Multicriteria Model for Diagnosing Dementia in People Infected with Human Immunodeficiency Virus |
title_full |
An Intelligent Multicriteria Model for Diagnosing Dementia in People Infected with Human Immunodeficiency Virus |
title_fullStr |
An Intelligent Multicriteria Model for Diagnosing Dementia in People Infected with Human Immunodeficiency Virus |
title_full_unstemmed |
An Intelligent Multicriteria Model for Diagnosing Dementia in People Infected with Human Immunodeficiency Virus |
title_sort |
intelligent multicriteria model for diagnosing dementia in people infected with human immunodeficiency virus |
publisher |
MDPI AG |
publishDate |
2021 |
url |
https://doaj.org/article/108fe08dc31341938bae07e846f3500d |
work_keys_str_mv |
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