sophIA: Platform to assist healthcare professionals in monitoring neonatal health - Morais, Flávio Leandro de; Canejo, Stephany Paula da Silva; Mello, Maria Eduarda Ferro de; Mendes, Katia Maria; Brandão Neto, Waldemar; Endo, Patricia Takako (Anais do Simpósio Brasileiro de Computação Aplicada à Saúde (SBCAS); 2026: Anais do XXVI Simpósio Brasileiro de Computação Aplicada à Saúde, 2026)
The neonatal period is marked by high vulnerability and significant morbidity and mortality, especially in the first days of life, requiring innovative strategies to improve the quality of care. This study presents sophIA, a platform under development based on Artificial Intelligence (AI) to support clinical decision-making in the Neonatal Intensive Care Unit. Its architecture integrates real clinical data, rigorous preparation, and predictive modeling using traditional and hybrid techniques, in addition to explainability mechanisms. The interface includes an interactive dashboard for indicator visualization and a support chatbot. The sophIA estimates risks for adverse neonatal outcomes and generates interpretable clinical alerts. Preliminary results indicate technical feasibility and methodological consistency, demonstrating improved performance and reliability. It is expected to contribute to more timely interventions, reduction of preventable complications, and strengthening of neonatal health management.