Artificial Intelligence technologies to manage obesity
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Vittalle (Online) |
Texto Completo: | https://periodicos.furg.br/vittalle/article/view/7654 |
Resumo: | In the last few decades, obesity has grown exponentially and it progression is imminent contributing to the increase of mortality levels. Artificial Intelligence (AI), which is Computer Science area, could be well applied to management of obesity, such as an important tool to avoid the threat caused by this disease. The aim of this literature review was to show AI applications to obesity management and discuss their effectiveness. The search was performed in the following databases: Public Medline (PubMed), Web of Science, Biblioteca Regional de Medicina (BIREME) and Google Academic, by using following keywords, “artificial intelligence” and “obesity”. Our results led to some Artificial Intelligence systems used in obesity handling, which were: the Decision Support System to bariatric surgery patients; the MOPET app to motivate physical activity; Parameter Decreasing Methods and Artificial Neural Network to correlate obesity to cardiovascular disease; Artificial Neural Network to predict resting energy expenditure; a Neuro-Fuzzy Model to refine body mass index result; an Image Processing Algorithm; and a Support Vector Machine that monitors food intake. In this review, all investigated AI systems may have a tendency to more accurate results indicating a promising tool to manage obesity and related diseases. |
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Artificial Intelligence technologies to manage obesityobesityartificial intelligencebody weightdisease managementIn the last few decades, obesity has grown exponentially and it progression is imminent contributing to the increase of mortality levels. Artificial Intelligence (AI), which is Computer Science area, could be well applied to management of obesity, such as an important tool to avoid the threat caused by this disease. The aim of this literature review was to show AI applications to obesity management and discuss their effectiveness. The search was performed in the following databases: Public Medline (PubMed), Web of Science, Biblioteca Regional de Medicina (BIREME) and Google Academic, by using following keywords, “artificial intelligence” and “obesity”. Our results led to some Artificial Intelligence systems used in obesity handling, which were: the Decision Support System to bariatric surgery patients; the MOPET app to motivate physical activity; Parameter Decreasing Methods and Artificial Neural Network to correlate obesity to cardiovascular disease; Artificial Neural Network to predict resting energy expenditure; a Neuro-Fuzzy Model to refine body mass index result; an Image Processing Algorithm; and a Support Vector Machine that monitors food intake. In this review, all investigated AI systems may have a tendency to more accurate results indicating a promising tool to manage obesity and related diseases.Universidade Federal do Rio Grande2018-09-27info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionRevisão de Literaturaapplication/pdfapplication/pdfhttps://periodicos.furg.br/vittalle/article/view/765410.14295/vittalle.v30i2.7654VITTALLE - Revista de Ciências da Saúde; v. 30 n. 2 (2018); 73-792177-78531413-3563reponame:Vittalle (Online)instname:Universidade Federal do Rio Grande (FURG)instacron:FURGenghttps://periodicos.furg.br/vittalle/article/view/7654/5403https://periodicos.furg.br/vittalle/article/view/7654/8097Copyright (c) 2018 VITTALLE - Revista de Ciências da Saúdeinfo:eu-repo/semantics/openAccessMarmett, BrunaCarvalho, Roseana BoekFortes, Melissa SantosCazella, Sílvio César2018-10-19T14:44:11Zoai:periodicos.furg.br:article/7654Revistahttps://periodicos.furg.br/vittallePUBhttps://periodicos.furg.br/vittalle/oaivittalle@furg.br2177-78531413-3563opendoar:2018-10-19T14:44:11Vittalle (Online) - Universidade Federal do Rio Grande (FURG)false |
dc.title.none.fl_str_mv |
Artificial Intelligence technologies to manage obesity |
title |
Artificial Intelligence technologies to manage obesity |
spellingShingle |
Artificial Intelligence technologies to manage obesity Marmett, Bruna obesity artificial intelligence body weight disease management |
title_short |
Artificial Intelligence technologies to manage obesity |
title_full |
Artificial Intelligence technologies to manage obesity |
title_fullStr |
Artificial Intelligence technologies to manage obesity |
title_full_unstemmed |
Artificial Intelligence technologies to manage obesity |
title_sort |
Artificial Intelligence technologies to manage obesity |
author |
Marmett, Bruna |
author_facet |
Marmett, Bruna Carvalho, Roseana Boek Fortes, Melissa Santos Cazella, Sílvio César |
author_role |
author |
author2 |
Carvalho, Roseana Boek Fortes, Melissa Santos Cazella, Sílvio César |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Marmett, Bruna Carvalho, Roseana Boek Fortes, Melissa Santos Cazella, Sílvio César |
dc.subject.por.fl_str_mv |
obesity artificial intelligence body weight disease management |
topic |
obesity artificial intelligence body weight disease management |
description |
In the last few decades, obesity has grown exponentially and it progression is imminent contributing to the increase of mortality levels. Artificial Intelligence (AI), which is Computer Science area, could be well applied to management of obesity, such as an important tool to avoid the threat caused by this disease. The aim of this literature review was to show AI applications to obesity management and discuss their effectiveness. The search was performed in the following databases: Public Medline (PubMed), Web of Science, Biblioteca Regional de Medicina (BIREME) and Google Academic, by using following keywords, “artificial intelligence” and “obesity”. Our results led to some Artificial Intelligence systems used in obesity handling, which were: the Decision Support System to bariatric surgery patients; the MOPET app to motivate physical activity; Parameter Decreasing Methods and Artificial Neural Network to correlate obesity to cardiovascular disease; Artificial Neural Network to predict resting energy expenditure; a Neuro-Fuzzy Model to refine body mass index result; an Image Processing Algorithm; and a Support Vector Machine that monitors food intake. In this review, all investigated AI systems may have a tendency to more accurate results indicating a promising tool to manage obesity and related diseases. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-09-27 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Revisão de Literatura |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://periodicos.furg.br/vittalle/article/view/7654 10.14295/vittalle.v30i2.7654 |
url |
https://periodicos.furg.br/vittalle/article/view/7654 |
identifier_str_mv |
10.14295/vittalle.v30i2.7654 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://periodicos.furg.br/vittalle/article/view/7654/5403 https://periodicos.furg.br/vittalle/article/view/7654/8097 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2018 VITTALLE - Revista de Ciências da Saúde info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2018 VITTALLE - Revista de Ciências da Saúde |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal do Rio Grande |
publisher.none.fl_str_mv |
Universidade Federal do Rio Grande |
dc.source.none.fl_str_mv |
VITTALLE - Revista de Ciências da Saúde; v. 30 n. 2 (2018); 73-79 2177-7853 1413-3563 reponame:Vittalle (Online) instname:Universidade Federal do Rio Grande (FURG) instacron:FURG |
instname_str |
Universidade Federal do Rio Grande (FURG) |
instacron_str |
FURG |
institution |
FURG |
reponame_str |
Vittalle (Online) |
collection |
Vittalle (Online) |
repository.name.fl_str_mv |
Vittalle (Online) - Universidade Federal do Rio Grande (FURG) |
repository.mail.fl_str_mv |
vittalle@furg.br |
_version_ |
1797041720449302528 |