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Improving patient referral classification through deep learning and natural language processing

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Resumo:The health sector is showing interest in machine learning techniques to enhance various aspects of patient care. In this paper, the application of deep learning and Natural Language Processing (NLP) techniques to improve patient referral classification at Hospital Garcia De Orta (HGO) is explored. Results showed that these advanced techniques outperformed traditional machine learning models, highlighting the effectiveness of combining deep learning and NLP.
Autores principais:Kamoun, Marouan
Assunto:Deep learning Natural language processing Classification Prediction Business analytics Machine learning
Ano:2024
País:Portugal
Tipo de documento:dissertação de mestrado
Tipo de acesso:acesso aberto
Instituição associada:Universidade Nova de Lisboa
Idioma:inglês
Origem:Repositório Institucional da UNL
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author Kamoun, Marouan
author_facet Kamoun, Marouan
author_role author
contributor_name_str_mv Xufre, Patrícia
Lavado, Susana
RUN
country_str PT
creators_json_txt [{\"Person.name\":\"Kamoun, Marouan\"}]
datacite.contributors.contributor.contributorName.fl_str_mv Xufre, Patrícia
Lavado, Susana
RUN
datacite.creators.creator.creatorName.fl_str_mv Kamoun, Marouan
datacite.date.Accepted.fl_str_mv 2024-02-02T00:00:00Z
datacite.date.available.fl_str_mv 2024-10-31T14:16:57Z
datacite.date.embargoed.fl_str_mv 2024-10-31T14:16:57Z
datacite.rights.fl_str_mv http://purl.org/coar/access_right/c_abf2
datacite.subjects.subject.fl_str_mv Deep learning
Natural language processing
Classification
Prediction
Business analytics
Machine learning
datacite.titles.title.fl_str_mv Improving patient referral classification through deep learning and natural language processing
dc.contributor.none.fl_str_mv Xufre, Patrícia
Lavado, Susana
RUN
dc.creator.none.fl_str_mv Kamoun, Marouan
dc.date.Accepted.fl_str_mv 2024-02-02T00:00:00Z
dc.date.available.fl_str_mv 2024-10-31T14:16:57Z
dc.date.embargoed.fl_str_mv 2024-10-31T14:16:57Z
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv http://hdl.handle.net/10362/174381
dc.language.none.fl_str_mv eng
dc.rights.none.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.subject.none.fl_str_mv Deep learning
Natural language processing
Classification
Prediction
Business analytics
Machine learning
dc.title.fl_str_mv Improving patient referral classification through deep learning and natural language processing
dc.type.none.fl_str_mv http://purl.org/coar/resource_type/c_bdcc
description The health sector is showing interest in machine learning techniques to enhance various aspects of patient care. In this paper, the application of deep learning and Natural Language Processing (NLP) techniques to improve patient referral classification at Hospital Garcia De Orta (HGO) is explored. Results showed that these advanced techniques outperformed traditional machine learning models, highlighting the effectiveness of combining deep learning and NLP.
dirty 0
eu_rights_str_mv openAccess
format masterThesis
fulltext.url.fl_str_mv https://run.unl.pt/bitstreams/efda1a1a-def8-4e17-a778-dea94231dd82/download
id run_7e6da9c22ee4f5889ebfbf562dbbb134
identifier.url.fl_str_mv http://hdl.handle.net/10362/174381
instacron_str unl
institution Universidade Nova de Lisboa
instname_str Universidade Nova de Lisboa
language eng
network_acronym_str run
network_name_str Repositório Institucional da UNL
oai_identifier_str oai:run.unl.pt:10362/174381
organization_str_mv urn:organizationAcronym:unl
person_str_mv Kamoun, Marouan
publishDate 2024
reponame_str Repositório Institucional da UNL
repository_id_str urn:repositoryAcronym:run
service_str_mv urn:repositoryAcronym:run
spelling engpt_PTThe health sector is showing interest in machine learning techniques to enhance various aspects of patient care. In this paper, the application of deep learning and Natural Language Processing (NLP) techniques to improve patient referral classification at Hospital Garcia De Orta (HGO) is explored. Results showed that these advanced techniques outperformed traditional machine learning models, highlighting the effectiveness of combining deep learning and NLP.application/pdfpt_PTImproving patient referral classification through deep learning and natural language processingKamoun, MarouanXufre, PatríciaLavado, SusanaHostingInstitutionOrganizationalRUNe-mailmailto:run@unl.ptrun@unl.ptURNurn:tid:2036053572024-10-31T14:16:57Z2024-02-022023-12-112024-02-02T00:00:00ZHandlehttp://hdl.handle.net/10362/174381http://purl.org/coar/access_right/c_abf2open accessDeep learningNatural language processingClassificationPredictionBusiness analyticsMachine learning2602728 bytesliteraturehttp://purl.org/coar/resource_type/c_bdccmaster thesishttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://run.unl.pt/bitstreams/efda1a1a-def8-4e17-a778-dea94231dd82/download
spellingShingle Improving patient referral classification through deep learning and natural language processing
Kamoun, Marouan
Deep learning
Natural language processing
Classification
Prediction
Business analytics
Machine learning
status SINGLETON
subject.fl_str_mv Deep learning
Natural language processing
Classification
Prediction
Business analytics
Machine learning
title Improving patient referral classification through deep learning and natural language processing
title_full Improving patient referral classification through deep learning and natural language processing
title_fullStr Improving patient referral classification through deep learning and natural language processing
title_full_unstemmed Improving patient referral classification through deep learning and natural language processing
title_short Improving patient referral classification through deep learning and natural language processing
title_sort Improving patient referral classification through deep learning and natural language processing
topic Deep learning
Natural language processing
Classification
Prediction
Business analytics
Machine learning
topic_facet Deep learning
Natural language processing
Classification
Prediction
Business analytics
Machine learning
url http://hdl.handle.net/10362/174381
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