Diagnosis of Gestational Diabetes Mellitus (GDM) Risk Using Artificial Intelligence in Pregnant Women Attended in Public Health Services: A Development and Validation Study.

• Grant number: 24/15609-5
• Support Opportunities: Scholarships in Brazil - Doctorate (Direct)
• Start date: June 01, 2025
• End date: May 31, 2029
• Field of knowledge: Health Sciences - Collective Health - Public Health
• Principal Investigator: Silvia Helena de Carvalho Sales Peres
• Grantee: Rharessa Gabrielly Ferreira Mendes
• Host Institution: Faculdade de Odontologia de Bauru (FOB). Universidade de São Paulo (USP). Bauru , SP, Brazil

Abstract

During pregnancy, significant changes occur in various aspects of a woman's life, requiring multidisciplinary monitoring. Excess weight can lead to several complications during pregnancy, making quality nutrition of utmost importance. Gestational weight gain includes maternal and fetal components and can increase the risk of Gestational Diabetes Mellitus (GDM) and periodontal diseases (PD). Periodontal disease, characterized by its inflammation, can increase the risk of GDM, making prenatal dental care essential. Therefore, this project aims to develop and validate software for the early detection of GDM using Artificial Intelligence, through the assessment of periodontal disease in pregnant women receiving care in the public health system. The study sample will consist of 125 pregnant women. They will be examined by researchers from CATO-USP (Advanced Translational Center for Obesity), a research and teaching center at the Bauru School of Dentistry. The study will divide participants into two groups: GD (with GDM) and GSD (without GDM). The use of Artificial Intelligence (AI) aims to enable the early diagnosis of GDM by analyzing oral health data and other factors, thereby improving disease management and reducing complications.