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Use of artificial intelligence in predicting gestational success based on the selection of physiological variables of patients undergoing assisted reproduction

Grant number: 19/26684-0
Support type:Scholarships in Brazil - Scientific Initiation
Effective date (Start): April 01, 2020
Effective date (End): March 31, 2021
Field of knowledge:Health Sciences - Medicine
Principal researcher:José Celso Rocha
Grantee:Eloiza Adriane Dal Molin
Home Institution: Faculdade de Ciências e Letras (FCL-ASSIS). Universidade Estadual Paulista (UNESP). Campus de Assis. Assis , SP, Brazil

Abstract

Artificial intelligence (AI) has experienced rapid growth in recent years, moving from the experimental phase to the implementation phase in various fields, including medicine. Therefore, advances in algorithms and learning theories and the availability of large data sets beyond computational power have contributed to advances in current AI applications. In the field of assisted reproduction, the applicability and increasing demand for AI is intrinsically related to the increase in the number of infertile couples nationally and internationally. Thus, the alliance between AI techniques, such as Artificial Neural Networks (RNAs) and Genetic Algorithms (GAs) is a strategy that has the ability to customize medical decisions for each specific infertility framework. However, for the construction of predictive models capable of being inserted in AI to achieve gestational success, it is necessary to survey several interfering variables in this process, such as the physiological factors of patients undergoing assisted reproduction. Thus, the present study aims to elucidate these characteristics and to the study the degrees of intensity towards gestational interference. Consequently, by relating physiological factors to the prognosis of pregnancy from a computational perspective, this research is an alternative for better assertiveness in diagnosis and medical treatment, also reducing the possible maternal and neonatal complications during and after pregnancy. (AU)

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