This paper is in the following e-collection/theme issue:

Artificial Intelligence (2313) Clinical Information and Decision Making (2046) Decision Support for Health Professionals (1618) Clinical Informatics (1418) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1799) Infectious Diseases (non-STD/STI) (1749) Hygiene and Infection Prevention (381) Nursing and Care for Patients with Infectious or Chronic Conditions (37) Artificial Intelligence, Machine Learning, and Natural Language Processing for Public Health (102) AI Applications in Public Health (36)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/58413, first published .
Development and Validation of Deep Learning–Based Infectivity Prediction in Pulmonary Tuberculosis Through Chest Radiography: Retrospective Study

Development and Validation of Deep Learning–Based Infectivity Prediction in Pulmonary Tuberculosis Through Chest Radiography: Retrospective Study

Development and Validation of Deep Learning–Based Infectivity Prediction in Pulmonary Tuberculosis Through Chest Radiography: Retrospective Study

Authors of this article:

Wou young Chung1 Author Orcid Image ;   Jinsik Yoon2 Author Orcid Image ;   Dukyong Yoon3, 4, 5 Author Orcid Image ;   Songsoo Kim3 Author Orcid Image ;   Yujeong Kim3 Author Orcid Image ;   Ji Eun Park1 Author Orcid Image ;   Young Ae Kang6 Author Orcid Image
Article Authors Cited by (4) Tweetations Metrics

Journals

  1. Zhang F, Han H, Li M, Tian T, Zhang G, Yang Z, Guo F, Li M, Wang Y, Wang J, Liu Y. Revolutionizing diagnosis of pulmonary Mycobacterium tuberculosis based on CT: a systematic review of imaging analysis through deep learning. Frontiers in Microbiology 2025;15 View
  2. Rudolph J, Huemmer C, Preuhs A, Buizza G, Dinkel J, Koliogiannis V, Fink N, Goller S, Schwarze V, Heimer M, Hoppe B, Liebig T, Ricke J, Sabel B, Rueckel J. Threshold optimization in AI chest radiography analysis: integrating real-world data and clinical subgroups. European Radiology Experimental 2025;9(1) View

Conference Proceedings

  1. Teja M, Singh D. 2025 12th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). TBNet: A Deep Learning Framework for Automated Tuberculosis Detection from Chest X-Ray Images View
  2. P R, Shalout I, Bhookya R, B S. 2025 5th International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT). Deep Learning–Based Detection and Analysis of Pulmonary Tuberculosis Using Structured Clinical Data for Enhanced Diagnostic Accuracy View