Choosing the most suitable classifier For supporting assistive technology adoption In people with Parkinson’s disease: a fuzzy Multi-criteria approach
Parkinson’s disease (PD) is the second most common neurodegenerative disorder which requires a long-term, interdisciplinary disease management. While there remains no cure for Parkinson’s disease, treatments are available to help reduce the main symptoms and maintain quality of life for as long as p...
- Autores:
-
Ortíz-Barrios, Miguel
Cleland, Ian
Donnelly, Mark
Greer, Jonathan
Petrillo, Antonella
Fernández-Mendoza, Zaury
Jaramillo-Rueda, Natalia
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2020
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/6904
- Acceso en línea:
- https://hdl.handle.net/11323/6904
https://repositorio.cuc.edu.co/
- Palabra clave:
- Parkinson’s disease (PD)
Technology adoption
Fuzzy Analytic Hierarchy Process (FAHP)
Decision making trial
Evaluation laboratory
- Rights
- openAccess
- License
- CC0 1.0 Universal
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|
dc.title.spa.fl_str_mv |
Choosing the most suitable classifier For supporting assistive technology adoption In people with Parkinson’s disease: a fuzzy Multi-criteria approach |
title |
Choosing the most suitable classifier For supporting assistive technology adoption In people with Parkinson’s disease: a fuzzy Multi-criteria approach |
spellingShingle |
Choosing the most suitable classifier For supporting assistive technology adoption In people with Parkinson’s disease: a fuzzy Multi-criteria approach Parkinson’s disease (PD) Technology adoption Fuzzy Analytic Hierarchy Process (FAHP) Decision making trial Evaluation laboratory |
title_short |
Choosing the most suitable classifier For supporting assistive technology adoption In people with Parkinson’s disease: a fuzzy Multi-criteria approach |
title_full |
Choosing the most suitable classifier For supporting assistive technology adoption In people with Parkinson’s disease: a fuzzy Multi-criteria approach |
title_fullStr |
Choosing the most suitable classifier For supporting assistive technology adoption In people with Parkinson’s disease: a fuzzy Multi-criteria approach |
title_full_unstemmed |
Choosing the most suitable classifier For supporting assistive technology adoption In people with Parkinson’s disease: a fuzzy Multi-criteria approach |
title_sort |
Choosing the most suitable classifier For supporting assistive technology adoption In people with Parkinson’s disease: a fuzzy Multi-criteria approach |
dc.creator.fl_str_mv |
Ortíz-Barrios, Miguel Cleland, Ian Donnelly, Mark Greer, Jonathan Petrillo, Antonella Fernández-Mendoza, Zaury Jaramillo-Rueda, Natalia |
dc.contributor.author.spa.fl_str_mv |
Ortíz-Barrios, Miguel Cleland, Ian Donnelly, Mark Greer, Jonathan Petrillo, Antonella Fernández-Mendoza, Zaury Jaramillo-Rueda, Natalia |
dc.subject.spa.fl_str_mv |
Parkinson’s disease (PD) Technology adoption Fuzzy Analytic Hierarchy Process (FAHP) Decision making trial Evaluation laboratory |
topic |
Parkinson’s disease (PD) Technology adoption Fuzzy Analytic Hierarchy Process (FAHP) Decision making trial Evaluation laboratory |
description |
Parkinson’s disease (PD) is the second most common neurodegenerative disorder which requires a long-term, interdisciplinary disease management. While there remains no cure for Parkinson’s disease, treatments are available to help reduce the main symptoms and maintain quality of life for as long as possible. Owing to the global burden faced by chronic conditions such as PD, Assistive technologies (AT’s) are becoming an increasingly common prescribed form of treatment. Low adoption is hampering the potential of digital technologies within health and social care. It is then necessary to employ classification algorithms have been developed for differentiating adopters and non-adopters of these technologies; thereby, potential negative effects on people with PD and cost overruns can be further minimized. This paper bridges this gap by extending the Multi-criteria decision-making approach adopted in technology adoption modeling for people with dementia. First, the fuzzy Analytic Hierarchy Process (FAHP) is applied to estimate the initial relative weights of criteria and sub-criteria. Then, the Decisionmaking Trial and Evaluation Laboratory (DEMATEL) is used for evaluating the interrelations and feedback among criteria and sub-criteria. The Technique for Order of Preferences by Similarity to Ideal Solution (TOPSIS) is finally implemented to rank three classifiers (Lazy IBk – knearest neighbors, Naïve bayes, and J48 decision tree) according to their ability to model technology adoption. A real case study considering is presented to validate the proposed approach. |
publishDate |
2020 |
dc.date.accessioned.none.fl_str_mv |
2020-08-11T00:20:22Z |
dc.date.available.none.fl_str_mv |
2020-08-11T00:20:22Z |
dc.date.issued.none.fl_str_mv |
2020 |
dc.type.spa.fl_str_mv |
Artículo de revista |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_2df8fbb1 |
dc.type.coar.spa.fl_str_mv |
http://purl.org/coar/resource_type/c_6501 |
dc.type.content.spa.fl_str_mv |
Text |
dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.redcol.spa.fl_str_mv |
http://purl.org/redcol/resource_type/ART |
dc.type.version.spa.fl_str_mv |
info:eu-repo/semantics/acceptedVersion |
format |
http://purl.org/coar/resource_type/c_6501 |
status_str |
acceptedVersion |
dc.identifier.uri.spa.fl_str_mv |
https://hdl.handle.net/11323/6904 |
dc.identifier.doi.spa.fl_str_mv |
DOI https://doi.org/10.1007/978-3-030-49907-5_28 |
dc.identifier.instname.spa.fl_str_mv |
Corporación Universidad de la Costa |
dc.identifier.reponame.spa.fl_str_mv |
REDICUC - Repositorio CUC |
dc.identifier.repourl.spa.fl_str_mv |
https://repositorio.cuc.edu.co/ |
url |
https://hdl.handle.net/11323/6904 https://repositorio.cuc.edu.co/ |
identifier_str_mv |
DOI https://doi.org/10.1007/978-3-030-49907-5_28 Corporación Universidad de la Costa REDICUC - Repositorio CUC |
dc.language.iso.none.fl_str_mv |
eng |
language |
eng |
dc.rights.spa.fl_str_mv |
CC0 1.0 Universal |
dc.rights.uri.spa.fl_str_mv |
http://creativecommons.org/publicdomain/zero/1.0/ |
dc.rights.accessrights.spa.fl_str_mv |
info:eu-repo/semantics/openAccess |
dc.rights.coar.spa.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
rights_invalid_str_mv |
CC0 1.0 Universal http://creativecommons.org/publicdomain/zero/1.0/ http://purl.org/coar/access_right/c_abf2 |
eu_rights_str_mv |
openAccess |
dc.publisher.spa.fl_str_mv |
Corporación Universidad de la Costa |
dc.source.spa.fl_str_mv |
Lecture Notes in Computer Science |
institution |
Corporación Universidad de la Costa |
dc.source.url.spa.fl_str_mv |
https://link.springer.com/chapter/10.1007/978-3-030-49907-5_28 |
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Ortíz-Barrios, MiguelCleland, IanDonnelly, MarkGreer, JonathanPetrillo, AntonellaFernández-Mendoza, ZauryJaramillo-Rueda, Natalia2020-08-11T00:20:22Z2020-08-11T00:20:22Z2020https://hdl.handle.net/11323/6904DOI https://doi.org/10.1007/978-3-030-49907-5_28Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/Parkinson’s disease (PD) is the second most common neurodegenerative disorder which requires a long-term, interdisciplinary disease management. While there remains no cure for Parkinson’s disease, treatments are available to help reduce the main symptoms and maintain quality of life for as long as possible. Owing to the global burden faced by chronic conditions such as PD, Assistive technologies (AT’s) are becoming an increasingly common prescribed form of treatment. Low adoption is hampering the potential of digital technologies within health and social care. It is then necessary to employ classification algorithms have been developed for differentiating adopters and non-adopters of these technologies; thereby, potential negative effects on people with PD and cost overruns can be further minimized. This paper bridges this gap by extending the Multi-criteria decision-making approach adopted in technology adoption modeling for people with dementia. First, the fuzzy Analytic Hierarchy Process (FAHP) is applied to estimate the initial relative weights of criteria and sub-criteria. Then, the Decisionmaking Trial and Evaluation Laboratory (DEMATEL) is used for evaluating the interrelations and feedback among criteria and sub-criteria. The Technique for Order of Preferences by Similarity to Ideal Solution (TOPSIS) is finally implemented to rank three classifiers (Lazy IBk – knearest neighbors, Naïve bayes, and J48 decision tree) according to their ability to model technology adoption. A real case study considering is presented to validate the proposed approach.Ortíz-Barrios, MiguelCleland, IanDonnelly, MarkGreer, JonathanPetrillo, AntonellaFernández-Mendoza, ZauryJaramillo-Rueda, NataliaengCorporación Universidad de la CostaCC0 1.0 Universalhttp://creativecommons.org/publicdomain/zero/1.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Lecture Notes in Computer Sciencehttps://link.springer.com/chapter/10.1007/978-3-030-49907-5_28Parkinson’s disease (PD)Technology adoptionFuzzy Analytic Hierarchy Process (FAHP)Decision making trialEvaluation laboratoryChoosing the most suitable classifier For supporting assistive technology adoption In people with Parkinson’s disease: a fuzzy Multi-criteria approachArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersionPublicationORIGINALChoosing the 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