Clinical validation of an artificial intelligence algorithm for classifying tuberculosis and pulmonary findings in chest radiographs

BackgroundChest X-ray (CXR) interpretation is critical in diagnosing various lung diseases. However, physicians, not specialists, are often the first ones to read them, frequently facing challenges in accurate interpretation. Artificial Intelligence (AI) algorithms could be of great help, but using...

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Main Authors:	Thiago Fellipe Ortiz de Camargo, Guilherme Alberto Sousa Ribeiro, Maria Carolina Bueno da Silva, Luan Oliveira da Silva, Pedro Paulo Teixeira e Silva Torres, Denise do Socorro Rodrigues da Silva, Mayler Olombrada Nunes de Santos, William Salibe Filho, Marcela Emer Egypto Rosa, Magdala de Araujo Novaes, Thiago Augusto Massarutto, Osvaldo Landi Junior, Elaine Yanata, Marcio Rodrigues da Cunha Reis, Gilberto Szarf, Pedro Vieira Santana Netto, Joselisa Peres Queiroz de Paiva
Format:	Article
Language:	English
Published:	Frontiers Media S.A. 2025-02-01
Series:	Frontiers in Artificial Intelligence
Subjects:	chest X-rays artificial intelligence deep learning clinical validation convolutional neural network
Online Access:	https://www.frontiersin.org/articles/10.3389/frai.2025.1512910/full
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Clinical validation of an artificial intelligence algorithm for classifying tuberculosis and pulmonary findings in chest radiographs

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