Automatic Information Extraction from Neurological Assessment Records for Leprosy Cases Using AI

• Jamilly Braga Melo IFPE
• Anthony Alexandre Morais Militão UPE
• Patricia Takako Endo UPE
• Hilson Gomes Vilar de Andrade IFPE / UPE

DOI: https://doi.org/10.5753/sbsi_estendido.2025.246799

Resumo

Leprosy is a chronic infectious disease that continues to be present in more than 120 countries. In 2023, over 20,000 new cases were reported in Brazil, making it the second most endemic country in the world. The development of new information systems that utilize available clinical records is essential to support decision-making during the treatment of this highly stigmatizing disease. In this study, we present preliminary results demonstrating the feasibility of using YOLO for the automatic recognition of non-textual data from neurological assessments of patients undergoing treatment. Our approach achieved an accuracy of 97.5% in recognizing sensory assessment records used in the Brazilian healthcare system.

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