MINING HEALTH – IDENTIFICATION, ANALYSIS AND PREDICTION SYSTEM FOR EARLY DISEASE DIAGNOSIS
Artificial intelligence, diseases, supplementary health, data mining; algorithm, prediction.
The Covid-19 pandemic has had global repercussions since its beginning in Wuhan, China, in 2019. With the resumption of postponed medical procedures, there has been a significant increase in hospitalizations, treatments and exams. The Institute of Supplementary Health Studies reported a 157% increase in healthcare spending in Brazil by 2030. This work proposes the development of Mining Health, a data mining platform to predict and diagnose diseases early, the information will be made available on updated dashboards so dynamics and reports with the option of spreadsheets, aiming to improve the health operator’s decision-making. Using an exploratory and explanatory approach with data from an operator in the northeast, descriptive statistics and classification algorithms in Python were used. Predictive models identify patterns, including patient demographic and behavioral variables, to target high-cost candidates. This project was selected in the health innovation program - LIGA - SEBRAE 2022.