Contribution of artificial intelligence to the imaging diagnosis of pediatric pulmonary tuberculosis.

Roberta Feijó Carvalho¹, Sandra Valéria Coelho da Silva¹, Michely Alexandrino de Souza Pinheiro¹, Rafaela Baroni Aurilio¹, Edwin Tao Ming Klinkenberg², Sara Vegas Viedma², Maria de Fátima Bazhuni Pombo Sant'Anna³, Ana Alice Amaral Ibiapina Parente¹, Claudete Aparecida Araújo Cardoso³, Clemax Couto Sant'Anna¹

¹Universidade Federal do Rio de Janeiro, Instituto de Puericultura e Pediatria Martagão Gesteira, Rio de Janeiro, Rio de Janeiro, Brazil.

²Delft Imaging Systems B.V., Hertogenbosch, The Netherlands.

³Universidade Federal Fluminense, Faculdade de Medicina, Niterói, Rio de Janeiro, Brazil.

PubMed PMC DOI PDF

Abstract

Pediatric tuberculosis (TB) remains a diagnostic challenge in Brazil and worldwide. The Brazilian Ministry of Health recommends a clinical scoring system (S-MoH) for children and adolescents with suspected TB. Interpretation of radiographs within this scoring system may require specialist input. AI-based systems, such as CAD4TB (Delft Imaging Systems B.V.), approved by the WHO for adults, are not…

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