In recent years the application of Machine Learning (ML) and Artificial Intelligence (AI) techniques in healthcare helped clinicians to improve the management of chronic patients. Diabetes is among the most common chronic illness in the world for which often is still challenging do an early detection and a correct classification of type of diabetes to an individual. In fact it often depends on the circumstances present at the time of diagnosis, and many diabetic individuals do not easily fit into a single class. The aim is this paper is the application of ML techniques in order to classify the occurrence of different mellitus diabetes on the base of clinical data obtained from diabetic patients during the daily hospitals activities.

Machine learning approaches for diabetes classification: Perspectives to artificial intelligence methods updating / Mainenti, G.; Campanile, L.; Marulli, F.; Ricciardi, C.; Valente, A. S.. - (2020), pp. 533-540. (Intervento presentato al convegno 5th International Conference on Internet of Things, Big Data and Security, IoTBDS 2020 nel 2020) [10.5220/0009839405330540].

Machine learning approaches for diabetes classification: Perspectives to artificial intelligence methods updating

Campanile L.;Marulli F.;Ricciardi C.;Valente A. S.
2020

Abstract

In recent years the application of Machine Learning (ML) and Artificial Intelligence (AI) techniques in healthcare helped clinicians to improve the management of chronic patients. Diabetes is among the most common chronic illness in the world for which often is still challenging do an early detection and a correct classification of type of diabetes to an individual. In fact it often depends on the circumstances present at the time of diagnosis, and many diabetic individuals do not easily fit into a single class. The aim is this paper is the application of ML techniques in order to classify the occurrence of different mellitus diabetes on the base of clinical data obtained from diabetic patients during the daily hospitals activities.
2020
Machine learning approaches for diabetes classification: Perspectives to artificial intelligence methods updating / Mainenti, G.; Campanile, L.; Marulli, F.; Ricciardi, C.; Valente, A. S.. - (2020), pp. 533-540. (Intervento presentato al convegno 5th International Conference on Internet of Things, Big Data and Security, IoTBDS 2020 nel 2020) [10.5220/0009839405330540].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/874357
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