Mobile Applications for Diabetes Self-Care and Approach to Machine Learning

Denis Cedeno-Moreno, Miguel Vargas-Lombardo

Abstract


Diabetes is a silent disease, the number of people who suffer from it increases daily, it is unfortunate that many young people develop this condition and do not know that they suffer from it. So much so that this disease is the fifth cause of death in Panama. Using software technologies applied to areas such as health every day is increasing. Scientific research in health areas, as well as the development of new technologies that involve smartphones and sensors, is making health self-care possible. Currently, interest in mobile health (mHealth) applications for disease self-care is growing. The innovation of technological tools associated with artificial intelligence is increasing every day. Among its most radical trends is machine learning, whose function is to develop techniques that allow computers to learn. This learning occurs through the data that can be provided to the algorithms responsible for categorizing. Therefore, this research aims to analyze mobile applications specifically those focused on diabetes, to propose an emerging systematic model of medical care for self-management of patients with diabetes and, finally, achieve a reliable data set with Panamanian patient data to apply machine-learning models and see how much we can help Panamanian doctors.


Keywords


Diabetes, machine learning, mHealth, artificial intelligence, mobile applications, self-care of health

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International Journal of Online and Biomedical Engineering (iJOE) – eISSN: 2626-8493
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