Supporting medical decisions for treating rare diseases through genetic programming

Detalhes bibliográficos
Autor(a) principal: Bakurov, Illya
Data de Publicação: 2019
Outros Autores: Castelli, Mauro, Vanneschi, Leonardo, Freitas, Maria João
Idioma: eng
Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Texto Completo: http://hdl.handle.net/10362/91519
Resumo: Bakurov, I., Castelli, M., Vanneschi, L., & Freitas, M. J. (2019). Supporting medical decisions for treating rare diseases through genetic programming. In P. Kaufmann, & P. A. Castillo (Eds.), Applications of Evolutionary Computation: 22nd International Conference, EvoApplications 2019, Held as Part of EvoStar 2019, Proceedings (pp. 187-203). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11454 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-16692-2_13. ISBN: 978-3-030-16691-5; Online ISBN: 978-3-030-16692-2
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spelling Supporting medical decisions for treating rare diseases through genetic programmingGenetic ProgrammingGeometric Semantic Genetic ProgrammingMedical decisionsRare diseasesTheoretical Computer ScienceComputer Science(all)SDG 3 - Good Health and Well-beingBakurov, I., Castelli, M., Vanneschi, L., & Freitas, M. J. (2019). Supporting medical decisions for treating rare diseases through genetic programming. In P. Kaufmann, & P. A. Castillo (Eds.), Applications of Evolutionary Computation: 22nd International Conference, EvoApplications 2019, Held as Part of EvoStar 2019, Proceedings (pp. 187-203). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11454 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-16692-2_13. ISBN: 978-3-030-16691-5; Online ISBN: 978-3-030-16692-2Casa dos Marcos is the largest specialized medical and residential center for rare diseases in the Iberian Peninsula. The large number of patients and the uniqueness of their diseases demand a considerable amount of diverse and highly personalized therapies, that are nowadays largely managed manually. This paper aims at catering for the emergent need of efficient and effective artificial intelligence systems for the support of the everyday activities of centers like Casa dos Marcos. We present six predictive data models developed with a genetic programming based system which, integrated into a web-application, enabled data-driven support for the therapists in Casa dos Marcos. The presented results clearly indicate the usefulness of the system in assisting complex therapeutic procedures for children suffering from rare diseases.Springer VerlagNOVA Information Management School (NOVA IMS)Information Management Research Center (MagIC) - NOVA Information Management SchoolRUNBakurov, IllyaCastelli, MauroVanneschi, LeonardoFreitas, Maria João2020-01-21T23:15:53Z2019-01-012019-01-01T00:00:00Zconference objectinfo:eu-repo/semantics/publishedVersion17application/pdfhttp://hdl.handle.net/10362/91519eng978-3-030-16691-50302-9743PURE: 13467192https://doi.org/10.1007/978-3-030-16692-2_13info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-22T17:43:00Zoai:run.unl.pt:10362/91519Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:14:29.472471Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Supporting medical decisions for treating rare diseases through genetic programming
title Supporting medical decisions for treating rare diseases through genetic programming
spellingShingle Supporting medical decisions for treating rare diseases through genetic programming
Bakurov, Illya
Genetic Programming
Geometric Semantic Genetic Programming
Medical decisions
Rare diseases
Theoretical Computer Science
Computer Science(all)
SDG 3 - Good Health and Well-being
title_short Supporting medical decisions for treating rare diseases through genetic programming
title_full Supporting medical decisions for treating rare diseases through genetic programming
title_fullStr Supporting medical decisions for treating rare diseases through genetic programming
title_full_unstemmed Supporting medical decisions for treating rare diseases through genetic programming
title_sort Supporting medical decisions for treating rare diseases through genetic programming
author Bakurov, Illya
author_facet Bakurov, Illya
Castelli, Mauro
Vanneschi, Leonardo
Freitas, Maria João
author_role author
author2 Castelli, Mauro
Vanneschi, Leonardo
Freitas, Maria João
author2_role author
author
author
dc.contributor.none.fl_str_mv NOVA Information Management School (NOVA IMS)
Information Management Research Center (MagIC) - NOVA Information Management School
RUN
dc.contributor.author.fl_str_mv Bakurov, Illya
Castelli, Mauro
Vanneschi, Leonardo
Freitas, Maria João
dc.subject.por.fl_str_mv Genetic Programming
Geometric Semantic Genetic Programming
Medical decisions
Rare diseases
Theoretical Computer Science
Computer Science(all)
SDG 3 - Good Health and Well-being
topic Genetic Programming
Geometric Semantic Genetic Programming
Medical decisions
Rare diseases
Theoretical Computer Science
Computer Science(all)
SDG 3 - Good Health and Well-being
description Bakurov, I., Castelli, M., Vanneschi, L., & Freitas, M. J. (2019). Supporting medical decisions for treating rare diseases through genetic programming. In P. Kaufmann, & P. A. Castillo (Eds.), Applications of Evolutionary Computation: 22nd International Conference, EvoApplications 2019, Held as Part of EvoStar 2019, Proceedings (pp. 187-203). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11454 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-16692-2_13. ISBN: 978-3-030-16691-5; Online ISBN: 978-3-030-16692-2
publishDate 2019
dc.date.none.fl_str_mv 2019-01-01
2019-01-01T00:00:00Z
2020-01-21T23:15:53Z
dc.type.driver.fl_str_mv conference object
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/91519
url http://hdl.handle.net/10362/91519
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 978-3-030-16691-5
0302-9743
PURE: 13467192
https://doi.org/10.1007/978-3-030-16692-2_13
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 17
application/pdf
dc.publisher.none.fl_str_mv Springer Verlag
publisher.none.fl_str_mv Springer Verlag
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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