Utilize este identificador para referenciar este registo: http://hdl.handle.net/10362/91519
Título: Supporting medical decisions for treating rare diseases through genetic programming
Autor: Bakurov, Illya
Castelli, Mauro
Vanneschi, Leonardo
Freitas, Maria João
Palavras-chave: Genetic Programming
Geometric Semantic Genetic Programming
Medical decisions
Rare diseases
Theoretical Computer Science
Computer Science(all)
SDG 3 - Good Health and Well-being
Data: 1-Jan-2019
Editora: Springer Verlag
Resumo: Casa 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.
Descrição: 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
Peer review: yes
URI: http://hdl.handle.net/10362/91519
DOI: https://doi.org/10.1007/978-3-030-16692-2_13
ISBN: 978-3-030-16691-5
978-3-030-16692-2
ISSN: 0302-9743
Aparece nas colecções:NIMS: MagIC - Documentos de conferências internacionais

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