Alchieri, João CarlosLira, Krisna de Aquino2024-05-132024-05-132024-03-07LIRA, Krisna de Aquino. Mining Health - sistema de identificação análise e previsão para diagnóstico antecipado de doenças. Orientador: Dr. João Carlos Alchieri. 2024. 86f. Dissertação (Mestrado Profissional em Ciência, Tecnologia e Inovação) - Escola de Ciências e Tecnologia, Universidade Federal do Rio Grande do Norte, Natal, 2024.https://repositorio.ufrn.br/handle/123456789/58319The Covid-19 pandemic has had global repercussions since it began in Wuhan, China, in 2019 and caused a significant impact on the Brazilian production chain, with supplementary healthcare being one of the most affected. Currently, with the resumption of postponed medical procedures, there is a significant increase in hospitalizations, treatments and exams. The supplementary health studies institute reported a 157% increase in healthcare spending in Brazil by 2030. This work proposes the development of the Mining Health data mining platform to predict and diagnose diseases early, using exploratory and explanatory data analysis . For development, open data made available by the Ministry of Health were used and descriptive and inferential statistics techniques, powerful libraries for data analysis and visualization were used using the Python programming language. Weka software was used to test the classification algorithms. Exploratory analyzes were able to classify patients most at risk of developing severe cases of Covid-19 or chronic diseases that affect quality of life, or that lead to longer hospitalization, improving the operator's ability to offer preventive and personalized care to their patients. beneficiaries, in addition to contributing significantly to cost reduction. The information is made available in dashboards and reports, aiming to improve decision-making for healthcare providers. The predictive analytics presented here offer crucial benefits in healthcare.Acesso AbertoMineração de dadosDoençasPythonSaúde suplementarAnálise preditivaInteligência artificialmasterThesisCNPQ::ENGENHARIAS