AI for detection of tuberculosis: Implications for global health

EJ Hwang, WG Jeong, PM David, M Arentz… - Radiology: Artificial …, 2024 - pubs.rsna.org
Tuberculosis, which primarily affects developing countries, remains a significant global
health concern. Since the 2010s, the role of chest radiography has expanded in tuberculosis …

Artificial intelligence-assisted double reading of chest radiographs to detect clinically relevant missed findings: a two-centre evaluation

L Topff, S Steltenpool, ER Ranschaert… - European …, 2024 - Springer
Objectives To evaluate an artificial intelligence (AI)–assisted double reading system for
detecting clinically relevant missed findings on routinely reported chest radiographs …

DIFDD: Deep intelligence framework for disease detection using patients electrocardiogram signals and X-ray images

S Goyal, R Singh - Multimedia Tools and Applications, 2024 - Springer
Heart disease has been the leading cause of mortality worldwide in the recent decade.
Since 2019, new lung-related infections have increased heart attack mortality. To minimize …

Deep learning model for pleural effusion detection via active learning and pseudo-labeling: a multisite study

J Chang, BR Lin, TH Wang, CM Chen - BMC Medical Imaging, 2024 - Springer
Background The study aimed to develop and validate a deep learning-based Computer
Aided Triage (CADt) algorithm for detecting pleural effusion in chest radiographs using an …

[PDF][PDF] Review on Abnormality Detection in Chest Radiograph

V Premalatha, VS Sai, K Anitha, AVK Vamsi, K Gayatri… - researchgate.net
Late detection of lung diseases can have severe consequences, including pneumonia, lung
opacity, and even death. Chest radiographs are essential tools for diagnosing these …