Banca de DEFESA: ERICK ODLANIER DO NASCIMENTO XAVIER CORTEZ

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
STUDENT : ERICK ODLANIER DO NASCIMENTO XAVIER CORTEZ
DATE: 27/01/2023
TIME: 09:30
LOCAL: Remoto
TITLE:

CHIA- Health plans Churn anaylsis using Machine learning 

KEY WORDS:

churn, health plans, machine learning 

PAGES: 69
BIG AREA: Ciências Exatas e da Terra
AREA: Ciência da Computação
SUMMARY:

In the last decades the growth of the internet and its technologies transforming the form of
relationship between companies and their customers. Acquiring a new customer costs a company
much more than his maintenance. Therefore, studies that allow this maintenance, or Churn
management, become important tools in the market. In the business model of health insurance
companies, competitiveness of market do companies to use processes and tools to help they to
making decisions for the future to increase their gains without losing their customer. For this, it is
necessary to verify the influence of the social characteristics of the users in the use of health plans,
and then uses Data Mining and artificial intelligence for this purpose. In this sense, the work in
question aims to use data mining and artificial intelligence in a study of case in a health plan
operator to analyze the influence of user characteristics on their adherence and retention. The
construction of the research and its methodology was developed using a set of data obtained from a
health operator, where these were used as samples for this study. After that, a normalization of
these data that were in different bases, as well as, immersed in different computational complexities
for its extraction. Thus, data mining methods were used with the help of Weka software to apply
artificial intelligence algorithms and models. in that real database. As a result, a micro software was
developed. services in the Python language, based on the results of data mining, which will serve as
a background for a system that meets the specific niche of Artificial Intelligence systems for health
plans. A construção da pesquisa e sua metodologia foi desenvolvida utilizando um conjunto de
dados obtidos de uma operadora de saúde, onde estes, foram utilizados como amostras para este
estudo.

COMMITTEE MEMBERS:
Presidente - 1885001 - ANNA GISELLE CAMARA DANTAS RIBEIRO RODRIGUES
Interno - 1943220 - ORIVALDO VIEIRA DE SANTANA JUNIOR
Externo ao Programa - 2488270 - RICARDO ALEXSANDRO DE MEDEIROS VALENTIM - UFRNExterno à Instituição - PAULO SCHOR - UNIFESP