dc.creatorSan Miguel Carrasco, Rafael (1)
dc.date.accessioned2017-10-23T16:13:43Z
dc.date.accessioned2023-03-07T19:14:40Z
dc.date.available2017-10-23T16:13:43Z
dc.date.available2023-03-07T19:14:40Z
dc.date.created2017-10-23T16:13:43Z
dc.identifier1989-1660
dc.identifierhttps://reunir.unir.net/handle/123456789/5817
dc.identifierhttp://dx.doi.org/10.9781/ijimai.2016.368
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/5900561
dc.description.abstractGeriatrics Medicine constitutes a clinical research field in which data analytics, particularly predictive modeling, can deliver compelling, reliable and long-lasting benefits, as well as non-intuitive clinical insights and net new knowledge. The research work described in this paper leverages predictive modeling to uncover new insights related to adverse reaction to drugs in elderly patients. The differentiation factor that sets this research exercise apart from traditional clinical research is the fact that it was not designed by formulating a particular hypothesis to be validated. Instead, it was data-centric, with data being mined to discover relationships or correlations among variables. Regression techniques were systematically applied to data through multiple iterations and under different configurations. The obtained results after the process was completed are explained and discussed next.
dc.languageeng
dc.publisherInternational Journal of Interactive Multimedia and Artificial Intelligence
dc.relation;vol. 3, nº 6
dc.relationhttp://www.ijimai.org/journal/node/939
dc.rightsopenAccess
dc.subjectgeriatrics
dc.subjectmedicine
dc.subjectdata analytics
dc.subjectstatistical analysis
dc.subjectpredictive modeling
dc.subjectknowledge management
dc.subjectadverse reactions
dc.subjectdrugs
dc.subjectEmerging
dc.subjectIJIMAI
dc.titleDetection of Adverse Reaction to Drugs in Elderly Patients through Predictive Modeling
dc.typeArticulo Revista Indexada


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