Publicación:
Mobile application: Expert systems model for disease prevention

dc.contributor.authorRubio-Paucar, Inoc
dc.contributor.authorRivas, Sttaly Ascona
dc.contributor.authorAndrade-Arenas, Laberiano
dc.contributor.authorHernández Celis, Domingo
dc.contributor.authorCabanillas-Carbonell, Michael A.
dc.date.accessioned2025-09-05T16:33:10Z
dc.description.abstractIn recent years, both locally and globally, many citizens are cornered by different diseases which grates a lot of concern in the person, due to the collapse of different medical centers, it is necessary to use information systems. The objective of the research is to develop a mobile application that allows detecting what type of disease a patient suffers from and maintaining communication with the expert in the field using an expert system such as azure machine learning studio that allows detecting the deadliest diseases. For the development of this research, the rup methodology was applied, which allows the use of different techniques where the necessary activities can be carried out with efficient communication. For the validation of this project, a survey was used for the experts with a questionnaire of questions, giving a positive result in the implementation of this project. The result was an acceptance of 83.3% in a high way in their survey responses. In conclusion, this mobile application was successfully designed, benefiting many people and, above all, preventing dangerous diseases that can even lead to death. © 2023 Elsevier B.V., All rights reserved.
dc.identifier.doi10.11591/eei.v12i5.5224
dc.identifier.scopus2-s2.0-85171244004
dc.identifier.urihttps://cris.uwiener.edu.pe/handle/001/295
dc.identifier.uuide05909f8-0741-4ab1-8b4c-5f268a7e9e4b
dc.language.isoen
dc.publisherInstitute of Advanced Engineering and Science
dc.relation.citationissue5
dc.relation.citationvolume12
dc.relation.ispartofseriesBulletin of Electrical Engineering and Informatics
dc.relation.issn23029285
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.titleMobile application: Expert systems model for disease prevention
dc.typehttp://purl.org/coar/resource_type/c_2df8fbb1
dspace.entity.typePublication
oaire.citation.endPage3052
oaire.citation.startPage3039

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