Diagnosis of diabetes mellitus in an E-health environment based on artificial neural network

dc.contributor.authorIbrahim, Farid
dc.contributor.authorAti, Modafar
dc.contributor.authorEl Nagar, Babikir
dc.date.accessioned2022-07-20T08:26:20Z
dc.date.accessioned2023-08-19T08:19:56Z
dc.date.available2022-07-20T08:26:20Z
dc.date.available2023-08-19T08:19:56Z
dc.date.issued2013-07
dc.description.abstractDiabetes is one of the modern chronic diseases that have a big impact on the life of a large number of populations across the world. According to the World Health Organization, it is estimated that this disease causes an annual death of up to 5% globally. Therefore there would be an urgent need to create system that is capable of aiding healthcare providers to monitor and then manage such chronic disease. Such a system requires a mechanism that helps the diagnosing of the patients and to participate in the aid of an eHealth management system. The aim of this research is to create such a mechanism upon the usage of Artificial Neural Networks that is capable of predicting the condition of a diabetic patient based on certain number of factors that are associated with such a chronic disease. The learning process was carried out using training cases that were extracted from local diabetic patients’ records. Specialized diabetes physicians were consulted in order to create an accurate training model. The latter model was then tested and results were evaluated and presented as part of this paper.en_US
dc.identifier.citationIbrahim, F., Ati, M., & El Nagar, B. (2013). Diagnosis of diabetes mellitus in an E-health environment based on artificial neural network. Journal of Next Generation Information Technology, 4(5), 125.en_US
dc.identifier.urihttps://edms.wexl.in/handle/1/3968
dc.language.isoenen_US
dc.publisherResearchGateen_US
dc.subjectArtificial neural networksen_US
dc.subjectMonitoring diabetesen_US
dc.subjectE-Healthen_US
dc.titleDiagnosis of diabetes mellitus in an E-health environment based on artificial neural networken_US
dc.title.alternativeJournal articleen_US
dc.typeArticleen_US

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