Identifying Diabetic Patient Profile Through Machine Learning-Based Clustering Analysis

Given the rapid growth over the past 15 years, Diabetes is currently a key issue in medical science and healthcare administration. Considering the importance of the health sector in our society, it is critical to correctly diagnose and treat Diabetes in order to avoid immediate difficulties and redu...

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Bibliographic Details
Main Authors: Gomes, João, Lopes, João, Guimarães, Tiago, Santos, Manuel Filipe
Format: Conference Proceeding
Language:English
Subjects:
Clustering
Diabetes
Machine Learning
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Summary:Given the rapid growth over the past 15 years, Diabetes is currently a key issue in medical science and healthcare administration. Considering the importance of the health sector in our society, it is critical to correctly diagnose and treat Diabetes in order to avoid immediate difficulties and reduce the chance of long-term issues. The analysis of vast amounts of data that are available in organizations is an important factor to describing their internal factors, predicting future trends, and prescribing the best course of action to improve their performance in light of the increasing technological evolution and the emergence of Artificial Intelligence (AI). The main objective of this project, which is being carried out in collaboration with the Unidade Local de Saúde do Alto Minho (ULSAM), is to define a typology of diabetic patients by building Machine Learning (ML) models from registered clinical information, medication, complementary diagnostic tools, therapeutic and monitoring data, and registered medication data.
ISSN:1877-0509
1877-0509
DOI:10.1016/j.procs.2023.03.116