Artificial intelligence in the diagnosis of neurodegenerative diseases: a systematic literature review

Detalhes bibliográficos
Autor(a) principal: Brito, Emilayne Nicácio Dias
Data de Publicação: 2021
Outros Autores: Figueiredo, Bárbara Queiroz de, Souto, Diego Nunes, Nogueira, Júlia Fernandes, Melo, Ana Luísa de Castro, Silva, Iorrane Tavares da, Oliveira, Iuri Pimenta, Almeida, Marcelo Gomes de
Tipo de documento: Artigo
Idioma: por
Título da fonte: Research, Society and Development
Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/20004
Resumo: Introduction: Artificial Intelligence (AI) is a branch of computer science that aims to develop systems that simulate the human capacity of perceiving a problem, identifying its components in order to solve problems and propose/make decisions. Objective: to expand knowledge and categorize applications of the use of AI for the diagnosis, treatment and prognosis of neurodegenerative diseases, since, currently, its use becomes widely applicable and essential to circumvent the stages of the disease. Methodology: This is a descriptive research of the integrative literature review type performed through online access in the National Library of Medicine (PubMed MEDLINE), Scientific Electronic Library Online (Scielo), Google Scholar, Virtual Health Library (VHL) databases), Web of Science and EBSCO Information Services, June and July 2021. Results and discussion: In recent years, data from neural networks, deep learning, and other mathematical methods are developing at unprecedented speed. They have been widely used in the field of image analysis, and have shown great potential in medical image analysis in the diagnosis of Alzheimer's Disease, Parkinson's Disease, Multiple Sclerosis, and the application of these methods can further improve the data analysis capability. complex multimodal imaging and improve the efficiency of these diagnoses. Conclusion: with artificial intelligence, neurodegenerative disorders can be investigated at a deeper level, providing a comprehensive overview of the disease and paving the way for the application of precision medicine to these pathologies.
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spelling Artificial intelligence in the diagnosis of neurodegenerative diseases: a systematic literature reviewInteligencia artificial en el diagnóstico de enfermedades neurodegenerativas: revisión sistemática de la literaturaInteligência Artificial no diagnóstico de doenças neurodegenerativas: uma revisão sistemática de literatura Inteligência artificialDoenças neurodegenerativasRessonância magnéticaDiagnóstico.Artificial intelligenceNeurodegenerative diseasesMagnetic resonanceDiagnosis.Inteligencia artificialEnfermedades neurodegenerativasResonancia magnéticaDiagnóstico.Introduction: Artificial Intelligence (AI) is a branch of computer science that aims to develop systems that simulate the human capacity of perceiving a problem, identifying its components in order to solve problems and propose/make decisions. Objective: to expand knowledge and categorize applications of the use of AI for the diagnosis, treatment and prognosis of neurodegenerative diseases, since, currently, its use becomes widely applicable and essential to circumvent the stages of the disease. Methodology: This is a descriptive research of the integrative literature review type performed through online access in the National Library of Medicine (PubMed MEDLINE), Scientific Electronic Library Online (Scielo), Google Scholar, Virtual Health Library (VHL) databases), Web of Science and EBSCO Information Services, June and July 2021. Results and discussion: In recent years, data from neural networks, deep learning, and other mathematical methods are developing at unprecedented speed. They have been widely used in the field of image analysis, and have shown great potential in medical image analysis in the diagnosis of Alzheimer's Disease, Parkinson's Disease, Multiple Sclerosis, and the application of these methods can further improve the data analysis capability. complex multimodal imaging and improve the efficiency of these diagnoses. Conclusion: with artificial intelligence, neurodegenerative disorders can be investigated at a deeper level, providing a comprehensive overview of the disease and paving the way for the application of precision medicine to these pathologies.Introducción: La Inteligencia Artificial (IA) es una rama de la informática que tiene como objetivo desarrollar sistemas que simulen la capacidad humana de percibir un problema, identificando sus componentes con el fin de resolver problemas y proponer / tomar decisiones. Objetivo: ampliar el conocimiento y categorizar las aplicaciones del uso de la IA para el diagnóstico, tratamiento y pronóstico de enfermedades neurodegenerativas, ya que, en la actualidad, su uso se vuelve ampliamente aplicable y fundamental para eludir las etapas de la enfermedad. Metodología: Se trata de una investigación descriptiva del tipo revisión integradora de la literatura realizada a través del acceso en línea en las bases de datos de la Biblioteca Nacional de Medicina (PubMed MEDLINE), Biblioteca Electrónica Científica en Línea (Scielo), Google Scholar, Biblioteca Virtual de Salud (BVS), Web de Science and EBSCO Information Services, junio y julio de 2021. Resultados y discusión: En los últimos años, los datos de las redes neuronales, el aprendizaje profundo y otros métodos matemáticos se están desarrollando a un ritmo sin precedentes. Se han utilizado ampliamente en el campo del análisis de imágenes y han demostrado un gran potencial en el análisis de imágenes médicas en el diagnóstico de la enfermedad de Alzheimer, la enfermedad de Parkinson, la esclerosis múltiple y la aplicación de estos métodos puede mejorar aún más la capacidad de análisis de datos. imágenes y mejorar la eficiencia de estos diagnósticos. Conclusión: con inteligencia artificial, los trastornos neurodegenerativos se pueden investigar a un nivel más profundo, proporcionando una visión global de la enfermedad y allanando el camino para la aplicación de la medicina de precisión a estas patologías.Introdução: Inteligência Artificial (IA) é um ramo da ciência da computação que se propõe a desenvolver sistemas que simulem a capacidade humana de percepção de um problema, identificando seus componentes para, com isso, resolver problemas e propor/tomar decisões. Objetivo: ampliar conhecimentos e categorizar aplicações do uso da IA para o diagnóstico, tratamento e prognóstico de doenças neurodegenerativas, uma vez que, atualmente, seu uso se torna amplamente aplicável e essencial para contornar as etapas da moléstia. Metodologia: Trata-se de uma pesquisa descritiva do tipo revisão integrativa da literatura realizada através do acesso online nas bases de dados National Library of Medicine (PubMed MEDLINE), Scientific Electronic Library Online (Scielo), Google Scholar, Biblioteca Virtual em Saúde (BVS), Web of Science e EBSCO Information Services, nos meses de junho e julho de 2021. Resultados e discussão: Nos últimos anos, os dados obtidos por redes neurais, aprendizagem profunda e outros métodos matemáticos estão se desenvolvendo a uma velocidade sem precedentes. Eles têm sido amplamente utilizados no campo da análise de imagens, e demostraram grande potencial na análise de imagens médicas no diagnóstico de Doença de Alzheimer, Doença de Parkinson, esclerose múltipla, sendo a aplicação destes métodos podem melhorar ainda mais a capacidade de análise de dados de imagem multimodais complexos e melhorar a eficiência desses diagnósticos.  Conclusão: com a inteligência artificial, os distúrbios neurodegenerativos podem ser investigados em um nível mais profundo, fornecendo uma visão geral abrangente da doença e abrindo caminhos para a aplicação da medicina de precisão para essas patologias.Research, Society and Development2021-09-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://rsdjournal.org/index.php/rsd/article/view/2000410.33448/rsd-v10i11.20004Research, Society and Development; Vol. 10 No. 11; e482101120004Research, Society and Development; Vol. 10 Núm. 11; e482101120004Research, Society and Development; v. 10 n. 11; e4821011200042525-3409reponame:Research, Society and Developmentinstname:Universidade Federal de Itajubá (UNIFEI)instacron:UNIFEIporhttps://rsdjournal.org/index.php/rsd/article/view/20004/17748Copyright (c) 2021 Emilayne Nicácio Dias Brito; Bárbara Queiroz de Figueiredo; Diego Nunes Souto; Júlia Fernandes Nogueira; Ana Luísa de Castro Melo; Iorrane Tavares da Silva; Iuri Pimenta Oliveira; Marcelo Gomes de Almeidahttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessBrito, Emilayne Nicácio DiasFigueiredo, Bárbara Queiroz de Souto, Diego NunesNogueira, Júlia FernandesMelo, Ana Luísa de CastroSilva, Iorrane Tavares da Oliveira, Iuri PimentaAlmeida, Marcelo Gomes de 2021-10-23T19:01:11Zoai:ojs.pkp.sfu.ca:article/20004Revistahttps://rsdjournal.org/index.php/rsd/indexPUBhttps://rsdjournal.org/index.php/rsd/oairsd.articles@gmail.com2525-34092525-3409opendoar:2024-01-17T09:39:46.246919Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)false
dc.title.none.fl_str_mv Artificial intelligence in the diagnosis of neurodegenerative diseases: a systematic literature review
Inteligencia artificial en el diagnóstico de enfermedades neurodegenerativas: revisión sistemática de la literatura
Inteligência Artificial no diagnóstico de doenças neurodegenerativas: uma revisão sistemática de literatura
title Artificial intelligence in the diagnosis of neurodegenerative diseases: a systematic literature review
spellingShingle Artificial intelligence in the diagnosis of neurodegenerative diseases: a systematic literature review
Brito, Emilayne Nicácio Dias
Inteligência artificial
Doenças neurodegenerativas
Ressonância magnética
Diagnóstico.
Artificial intelligence
Neurodegenerative diseases
Magnetic resonance
Diagnosis.
Inteligencia artificial
Enfermedades neurodegenerativas
Resonancia magnética
Diagnóstico.
title_short Artificial intelligence in the diagnosis of neurodegenerative diseases: a systematic literature review
title_full Artificial intelligence in the diagnosis of neurodegenerative diseases: a systematic literature review
title_fullStr Artificial intelligence in the diagnosis of neurodegenerative diseases: a systematic literature review
title_full_unstemmed Artificial intelligence in the diagnosis of neurodegenerative diseases: a systematic literature review
title_sort Artificial intelligence in the diagnosis of neurodegenerative diseases: a systematic literature review
author Brito, Emilayne Nicácio Dias
author_facet Brito, Emilayne Nicácio Dias
Figueiredo, Bárbara Queiroz de
Souto, Diego Nunes
Nogueira, Júlia Fernandes
Melo, Ana Luísa de Castro
Silva, Iorrane Tavares da
Oliveira, Iuri Pimenta
Almeida, Marcelo Gomes de
author_role author
author2 Figueiredo, Bárbara Queiroz de
Souto, Diego Nunes
Nogueira, Júlia Fernandes
Melo, Ana Luísa de Castro
Silva, Iorrane Tavares da
Oliveira, Iuri Pimenta
Almeida, Marcelo Gomes de
author2_role author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Brito, Emilayne Nicácio Dias
Figueiredo, Bárbara Queiroz de
Souto, Diego Nunes
Nogueira, Júlia Fernandes
Melo, Ana Luísa de Castro
Silva, Iorrane Tavares da
Oliveira, Iuri Pimenta
Almeida, Marcelo Gomes de
dc.subject.por.fl_str_mv Inteligência artificial
Doenças neurodegenerativas
Ressonância magnética
Diagnóstico.
Artificial intelligence
Neurodegenerative diseases
Magnetic resonance
Diagnosis.
Inteligencia artificial
Enfermedades neurodegenerativas
Resonancia magnética
Diagnóstico.
topic Inteligência artificial
Doenças neurodegenerativas
Ressonância magnética
Diagnóstico.
Artificial intelligence
Neurodegenerative diseases
Magnetic resonance
Diagnosis.
Inteligencia artificial
Enfermedades neurodegenerativas
Resonancia magnética
Diagnóstico.
description Introduction: Artificial Intelligence (AI) is a branch of computer science that aims to develop systems that simulate the human capacity of perceiving a problem, identifying its components in order to solve problems and propose/make decisions. Objective: to expand knowledge and categorize applications of the use of AI for the diagnosis, treatment and prognosis of neurodegenerative diseases, since, currently, its use becomes widely applicable and essential to circumvent the stages of the disease. Methodology: This is a descriptive research of the integrative literature review type performed through online access in the National Library of Medicine (PubMed MEDLINE), Scientific Electronic Library Online (Scielo), Google Scholar, Virtual Health Library (VHL) databases), Web of Science and EBSCO Information Services, June and July 2021. Results and discussion: In recent years, data from neural networks, deep learning, and other mathematical methods are developing at unprecedented speed. They have been widely used in the field of image analysis, and have shown great potential in medical image analysis in the diagnosis of Alzheimer's Disease, Parkinson's Disease, Multiple Sclerosis, and the application of these methods can further improve the data analysis capability. complex multimodal imaging and improve the efficiency of these diagnoses. Conclusion: with artificial intelligence, neurodegenerative disorders can be investigated at a deeper level, providing a comprehensive overview of the disease and paving the way for the application of precision medicine to these pathologies.
publishDate 2021
dc.date.none.fl_str_mv 2021-09-07
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://rsdjournal.org/index.php/rsd/article/view/20004
10.33448/rsd-v10i11.20004
url https://rsdjournal.org/index.php/rsd/article/view/20004
identifier_str_mv 10.33448/rsd-v10i11.20004
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://rsdjournal.org/index.php/rsd/article/view/20004/17748
dc.rights.driver.fl_str_mv https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Research, Society and Development
publisher.none.fl_str_mv Research, Society and Development
dc.source.none.fl_str_mv Research, Society and Development; Vol. 10 No. 11; e482101120004
Research, Society and Development; Vol. 10 Núm. 11; e482101120004
Research, Society and Development; v. 10 n. 11; e482101120004
2525-3409
reponame:Research, Society and Development
instname:Universidade Federal de Itajubá (UNIFEI)
instacron:UNIFEI
instname_str Universidade Federal de Itajubá (UNIFEI)
instacron_str UNIFEI
institution UNIFEI
reponame_str Research, Society and Development
collection Research, Society and Development
repository.name.fl_str_mv Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)
repository.mail.fl_str_mv rsd.articles@gmail.com
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