Multi-view deep learning framework for the detection of chest X-rays compatible with pediatric pulmonary tuberculosis

Tuberculosis (TB) remains a major global health burden, particularly in low-resource, high-prevalence regions. Pediatric TB diagnosis poses challenges with non-specific symptoms and less distinct radiological manifestations than adult TB. Many affected children remain undiagnosed or untreated. The W...

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Bibliographic Details
Published in:	Nature communications Vol. 16; no. 1; pp. 9170 - 16
Main Authors:	Capellán-Martín, Daniel, Gómez-Valverde, Juan J., Sánchez-Jacob, Ramón, Hernanz-Lobo, Alicia, Schaaf, H. Simon, García-Delgado, Lara, Augusto, Orvalho, Roshanitabrizi, Pooneh, García-Basteiro, Alberto L., Ribó, Jose Luis, Lancharro, Ángel, Noguera-Julian, Antoni, Blázquez-Gamero, Daniel, Linguraru, Marius George, Santiago-García, Begoña, López-Varela, Elisa, Ledesma-Carbayo, María J.
Format:	Journal Article
Language:	English
Published:	London Nature Publishing Group UK 27.10.2025 Nature Publishing Group Nature Portfolio
Subjects:	639/166/985 639/705/117 692/308/3187 692/699/255/1856 Abnormalities Adolescent Age Age groups Artificial intelligence Assessments Chest Child Child, Preschool Classification Clinical medicine Compatibility Coronaviruses Datasets Deep Learning Diagnosis Disease Female Global health Humanities and Social Sciences Humans Infant Male Medical diagnosis multidisciplinary Pandemics Pediatrics Public health Radiography, Thoracic - methods Science Science (multidisciplinary) Tuberculosis Tuberculosis, Pulmonary - diagnosis Tuberculosis, Pulmonary - diagnostic imaging X-rays
ISSN:	2041-1723, 2041-1723
Online Access:	Get full text
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