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 Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: April 01, 2020
• End date: March 31, 2021
• Field of knowledge: Health Sciences - Medicine
• Principal Investigator: José Celso Rocha
• Grantee: Eloiza Adriane Dal Molin
• Host 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)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

CHELES, DORIS SPINOSA; FERREIRA, ANDRE SATOSHI; DE JESUS, ISABELA SUEITT; FERNANDEZ, ELEONORA INACIO; PINHEIRO, GABRIEL MARTINS; DAL MOLIN, ELOIZA ADRIANE; ALVES, WALLACE; MILANEZI DE SOUZA, REBECA COLAUTO; BORI, LORENA; MESEGUER, MARCOS; et al. An Image Processing Protocol to Extract Variables Predictive of Human Embryo Fitness for Assisted Reproduction. APPLIED SCIENCES-BASEL, v. 12, n. 7, p. 20-pg., 2022-04-01. (20/07634-9, 18/24252-2, 19/26749-4, 17/19323-5, 19/26684-0)