Nonlinear Systems in Healthcare towards Intelligent Disease Prediction

Chatterjee, Parag - Cymberknop, Leandro - Armentano, Ricardo

Resumen:

Healthcare is one of the key fields that works quite strongly with advanced analytical techniques for prediction of diseases and risks. Data being the most important asset in recent times, a huge amount of health data is being collected, thanks to the recent advancements of IoT, smart healthcare, etc. But the focal objective lies in making sense of that data and to obtain knowledge, using intelligent analytics. Nonlinear systems find use specifically in this field, working closely with health data. Using advanced methods of machine learning and computational intelligence, nonlinear analysis performs a key role in analyzing the enormous amount of data, aimed at finding important patterns and predicting diseases. Especially in the field of smart healthcare, this chapter explores some aspects of nonlinear systems in predictive analytics, providing a holistic view of the field as well as some examples to illustrate such intelligent systems toward disease prediction.


Detalles Bibliográficos
2019
Agencia Nacional de Investigación e Innovación (ANII), Uruguay
Universidad Tecnológica Nacional, Buenos Aires, Argentina
Universidad de la República, Uruguay
nonlinear systems
healthcare
artificial intelligence
computational intelligence
machine learning
predictive analytics
chronic disease
cancer
cardiometabolic disease
Parkinson’s disease
Ciencias Médicas y de la Salud
Ciencias Naturales y Exactas
Ciencias de la Computación e Información
Ingeniería y Tecnología
Inglés
Agencia Nacional de Investigación e Innovación
REDI
https://hdl.handle.net/20.500.12381/285
https://www.intechopen.com/books/nonlinear-systems-theoretical-aspects-and-recent-applications/nonlinear-systems-in-healthcare-towards-intelligent-disease-prediction
Acceso abierto
Reconocimiento-NoComercial-SinObraDerivada 4.0 Internacional. (CC BY-NC-ND)
_version_ 1814959257750077440
author Chatterjee, Parag
author2 Cymberknop, Leandro
Armentano, Ricardo
author2_role author
author
author_facet Chatterjee, Parag
Cymberknop, Leandro
Armentano, Ricardo
author_role author
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58850557a3884a481cb9dc478047fdd0
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
bitstream.url.fl_str_mv https://redi.anii.org.uy/jspui/bitstream/20.500.12381/285/2/license.txt
https://redi.anii.org.uy/jspui/bitstream/20.500.12381/285/1/IntechOpen%20Full%20Chapter.pdf
collection REDI
dc.creator.none.fl_str_mv Chatterjee, Parag
Cymberknop, Leandro
Armentano, Ricardo
dc.date.accessioned.none.fl_str_mv 2021-05-12T23:43:10Z
dc.date.available.none.fl_str_mv 2021-05-12T23:43:10Z
dc.date.issued.none.fl_str_mv 2019-09-03
dc.description.abstract.none.fl_txt_mv Healthcare is one of the key fields that works quite strongly with advanced analytical techniques for prediction of diseases and risks. Data being the most important asset in recent times, a huge amount of health data is being collected, thanks to the recent advancements of IoT, smart healthcare, etc. But the focal objective lies in making sense of that data and to obtain knowledge, using intelligent analytics. Nonlinear systems find use specifically in this field, working closely with health data. Using advanced methods of machine learning and computational intelligence, nonlinear analysis performs a key role in analyzing the enormous amount of data, aimed at finding important patterns and predicting diseases. Especially in the field of smart healthcare, this chapter explores some aspects of nonlinear systems in predictive analytics, providing a holistic view of the field as well as some examples to illustrate such intelligent systems toward disease prediction.
dc.description.sponsorship.none.fl_txt_mv Agencia Nacional de Investigación e Innovación (ANII), Uruguay
Universidad Tecnológica Nacional, Buenos Aires, Argentina
Universidad de la República, Uruguay
dc.identifier.anii.es.fl_str_mv FSDA_1_2017_1_143653
dc.identifier.doi.none.fl_str_mv 10.5772/intechopen.88163
dc.identifier.isbn.none.fl_str_mv 978-1-78985-472-5
978-1-83880-308-7
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12381/285
dc.identifier.url.none.fl_str_mv https://www.intechopen.com/books/nonlinear-systems-theoretical-aspects-and-recent-applications/nonlinear-systems-in-healthcare-towards-intelligent-disease-prediction
dc.language.iso.none.fl_str_mv eng
dc.publisher.es.fl_str_mv IntechOpen
dc.rights.es.fl_str_mv Acceso abierto
dc.rights.license.none.fl_str_mv Reconocimiento-NoComercial-SinObraDerivada 4.0 Internacional. (CC BY-NC-ND)
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
dc.source.es.fl_str_mv Nonlinear Systems — Theoretical Aspects and Recent Applications
dc.source.none.fl_str_mv reponame:REDI
instname:Agencia Nacional de Investigación e Innovación
instacron:Agencia Nacional de Investigación e Innovación
dc.subject.anii.es.fl_str_mv Ciencias Médicas y de la Salud
Ciencias Naturales y Exactas
Ciencias de la Computación e Información
Ingeniería y Tecnología
dc.subject.es.fl_str_mv nonlinear systems
healthcare
artificial intelligence
computational intelligence
machine learning
predictive analytics
chronic disease
cancer
cardiometabolic disease
Parkinson’s disease
dc.title.none.fl_str_mv Nonlinear Systems in Healthcare towards Intelligent Disease Prediction
dc.type.es.fl_str_mv Parte de libro
dc.type.none.fl_str_mv info:eu-repo/semantics/bookPart
dc.type.version.es.fl_str_mv Publicado
dc.type.version.none.fl_str_mv info:eu-repo/semantics/publishedVersion
description Healthcare is one of the key fields that works quite strongly with advanced analytical techniques for prediction of diseases and risks. Data being the most important asset in recent times, a huge amount of health data is being collected, thanks to the recent advancements of IoT, smart healthcare, etc. But the focal objective lies in making sense of that data and to obtain knowledge, using intelligent analytics. Nonlinear systems find use specifically in this field, working closely with health data. Using advanced methods of machine learning and computational intelligence, nonlinear analysis performs a key role in analyzing the enormous amount of data, aimed at finding important patterns and predicting diseases. Especially in the field of smart healthcare, this chapter explores some aspects of nonlinear systems in predictive analytics, providing a holistic view of the field as well as some examples to illustrate such intelligent systems toward disease prediction.
eu_rights_str_mv openAccess
format bookPart
id REDI_483fc45729b5512f061342dff87b030f
identifier_str_mv 978-1-78985-472-5
978-1-83880-308-7
FSDA_1_2017_1_143653
10.5772/intechopen.88163
instacron_str Agencia Nacional de Investigación e Innovación
institution Agencia Nacional de Investigación e Innovación
instname_str Agencia Nacional de Investigación e Innovación
language eng
network_acronym_str REDI
network_name_str REDI
oai_identifier_str oai:redi.anii.org.uy:20.500.12381/285
publishDate 2019
reponame_str REDI
repository.mail.fl_str_mv jmaldini@anii.org.uy
repository.name.fl_str_mv REDI - Agencia Nacional de Investigación e Innovación
repository_id_str 9421
rights_invalid_str_mv Reconocimiento-NoComercial-SinObraDerivada 4.0 Internacional. (CC BY-NC-ND)
Acceso abierto
spelling Reconocimiento-NoComercial-SinObraDerivada 4.0 Internacional. (CC BY-NC-ND)Acceso abiertoinfo:eu-repo/semantics/openAccess2021-05-12T23:43:10Z2021-05-12T23:43:10Z2019-09-03978-1-78985-472-5978-1-83880-308-7https://hdl.handle.net/20.500.12381/285FSDA_1_2017_1_14365310.5772/intechopen.88163https://www.intechopen.com/books/nonlinear-systems-theoretical-aspects-and-recent-applications/nonlinear-systems-in-healthcare-towards-intelligent-disease-predictionHealthcare is one of the key fields that works quite strongly with advanced analytical techniques for prediction of diseases and risks. Data being the most important asset in recent times, a huge amount of health data is being collected, thanks to the recent advancements of IoT, smart healthcare, etc. But the focal objective lies in making sense of that data and to obtain knowledge, using intelligent analytics. Nonlinear systems find use specifically in this field, working closely with health data. Using advanced methods of machine learning and computational intelligence, nonlinear analysis performs a key role in analyzing the enormous amount of data, aimed at finding important patterns and predicting diseases. Especially in the field of smart healthcare, this chapter explores some aspects of nonlinear systems in predictive analytics, providing a holistic view of the field as well as some examples to illustrate such intelligent systems toward disease prediction.Agencia Nacional de Investigación e Innovación (ANII), UruguayUniversidad Tecnológica Nacional, Buenos Aires, ArgentinaUniversidad de la República, UruguayengIntechOpenNonlinear Systems — Theoretical Aspects and Recent Applicationsreponame:REDIinstname:Agencia Nacional de Investigación e Innovacióninstacron:Agencia Nacional de Investigación e Innovaciónnonlinear systemshealthcareartificial intelligencecomputational intelligencemachine learningpredictive analyticschronic diseasecancercardiometabolic diseaseParkinson’s diseaseCiencias Médicas y de la SaludCiencias Naturales y ExactasCiencias de la Computación e InformaciónIngeniería y TecnologíaNonlinear Systems in Healthcare towards Intelligent Disease PredictionParte de libroPublicadoinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bookPartUniversidad Tecnológica Nacional, Buenos Aires, Argentina/ / Ciencias Médicas y de la Salud/ / Ciencias Naturales y Exactas / Ciencias de la Computación e Información/ / Ingeniería y TecnologíaChatterjee, ParagCymberknop, LeandroArmentano, RicardoLICENSElicense.txtlicense.txttext/plain; charset=utf-84746https://redi.anii.org.uy/jspui/bitstream/20.500.12381/285/2/license.txt2d97768b1a25a7df5a347bb58fd2d77fMD52ORIGINALIntechOpen Full Chapter.pdfIntechOpen Full Chapter.pdfFull Chapterapplication/pdf543497https://redi.anii.org.uy/jspui/bitstream/20.500.12381/285/1/IntechOpen%20Full%20Chapter.pdf58850557a3884a481cb9dc478047fdd0MD5120.500.12381/2852021-08-01 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- Agencia Nacional de Investigación e Innovaciónfalse
spellingShingle Nonlinear Systems in Healthcare towards Intelligent Disease Prediction
Chatterjee, Parag
nonlinear systems
healthcare
artificial intelligence
computational intelligence
machine learning
predictive analytics
chronic disease
cancer
cardiometabolic disease
Parkinson’s disease
Ciencias Médicas y de la Salud
Ciencias Naturales y Exactas
Ciencias de la Computación e Información
Ingeniería y Tecnología
status_str publishedVersion
title Nonlinear Systems in Healthcare towards Intelligent Disease Prediction
title_full Nonlinear Systems in Healthcare towards Intelligent Disease Prediction
title_fullStr Nonlinear Systems in Healthcare towards Intelligent Disease Prediction
title_full_unstemmed Nonlinear Systems in Healthcare towards Intelligent Disease Prediction
title_short Nonlinear Systems in Healthcare towards Intelligent Disease Prediction
title_sort Nonlinear Systems in Healthcare towards Intelligent Disease Prediction
topic nonlinear systems
healthcare
artificial intelligence
computational intelligence
machine learning
predictive analytics
chronic disease
cancer
cardiometabolic disease
Parkinson’s disease
Ciencias Médicas y de la Salud
Ciencias Naturales y Exactas
Ciencias de la Computación e Información
Ingeniería y Tecnología
url https://hdl.handle.net/20.500.12381/285
https://www.intechopen.com/books/nonlinear-systems-theoretical-aspects-and-recent-applications/nonlinear-systems-in-healthcare-towards-intelligent-disease-prediction