Artificial Intelligence in the Clinical Monitoring and Management of Pregnant Women with Gestational Diabetes and Hypertension

• Grant number: 25/20621-7
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: December 01, 2025
• End date: November 30, 2026
• Field of knowledge: Health Sciences - Medicine - Maternal and Child Health
• Principal Investigator: Luciana Neves Cosenso Martin
• Grantee: Letícia Aguirre Mantoani
• Host Institution: Faculdade de Medicina de São José do Rio Preto (FAMERP). São José do Rio Preto , SP, Brazil

Abstract

Introduction: Artificial intelligence (AI) has been used in medicine to improve diagnoses and treatments. Remote monitoring of pregnant women with gestational diabetes mellitus (GDM) enables early interventions and improved follow-up, aiming at better health outcomes. Objective: To evaluate the impact of the use of AI in the education, monitoring, and treatment of GDM in reducing maternal and fetal complications among patients at the high-risk prenatal clinic of FAMERP/FUNFARME, São José do Rio Preto, Brazil. Additionally, to assess the prevalence of hypertension in the study sample. Methods: This is a clinical, interventional, longitudinal, and prospective study to evaluate the use of AI through WhatsApp® Messenger for education and management of GDM, compared with pregnant women followed in the same center during the previous two years without the AI tool. The study was approved by the local Research Ethics Committee. The AI tool was developed by a company under the scientific supervision of the obstetrician researcher responsible for patient care. Eligible participants include pregnant women diagnosed with GDM who consent to participate. Exclusion criteria: pregnant women with severe pre-existing conditions or incomplete medical records. The following parameters will be evaluated: gestational age at the beginning and at delivery, fetal death, birthweight, need for neonatal intensive care unit admission, neonatal hypoglycemia, maternal weight gain,delivery route, gestational hypertension, and history of miscarriage. The AI system provides educational materials on diabetes, records self-reported capillary blood glucose levels, generates weekly glycemic control charts, and supports medical decision-making through an embedded algorithm. Conclusion: Through an innovative and low-cost AI-based tool, the study aims to improve the management of patients with GDM and reduce maternal-fetal complications.