Artificial Intelligence Applied to Rare Diseases: Optimizing the Diagnostic Itinerary in the Care Network

• Grant number: 24/19360-1
• Support Opportunities: Scholarships in Brazil - Master
• Start date: January 01, 2025
• End date: December 31, 2026
• Field of knowledge: Health Sciences - Collective Health - Public Health
• Principal Investigator: Domingos Alves
• Grantee: Letícia Fontanelli Straube de Souza
• Host Institution: Faculdade de Medicina de Ribeirão Preto (FMRP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil
• Associated research grant: 23/10203-8 - Promoting Comprehensive Care for People with Rare Diseases: Strengthening the Care, Registration and Awareness Network at Hospital das Clínicas in Ribeirão Preto, AP.PP
• Associated scholarship(s): 25/24181-1 - Temporal Data Mining of The Rare Disease Patient Journey in Brazil, BE.EP.MS

Abstract

Artificial Intelligence (AI) has the potential to transform medicine through new possibilities for the diagnosis, management and treatment of diseases, including rare diseases (RDs). These conditions affect a small portion of the population, resulting in major challenges in terms of diagnosis and treatment. In particular, there is great difficulty in diagnosing RDs, as they often remain undetected or treated as common diseases, which hinders the accuracy of prevalence estimates, among other outcomes (e.g., morbidity, mortality). In Brazil, despite great advances in diagnosis, mainly due to new technologies and the recently approved policy for the care of RDs, there is a scarcity of national epidemiological data, and the data available in the literature are restricted to specific disorders or regions, mainly derived from the efforts of the scientific community. That said, this project aims to apply AI techniques to the development of innovative tools to support diagnosis and interventions in the field of RDs, also aiming to improve the collection, organization and quality of information in this area.