Vendor source
Reviewed 28 Sept 2026
Completeness Strong (72%)
To detect tuberculosis-related abnormalities in posterior anterior chest X-rays, Delft Imaging and Thirona developed CAD4TB™. This computer-aided detection software takes a single chest X-ray as its input, in the form of a DICOM image, and produces several outputs: a quality assessment of the input image, a heat map highlighting possible abnormal areas, and a score between 0 and 100 indicating the likelihood of the X-ray being abnormal and the subject on the X-ray being affected by tuberculosis.
Supported by 21 papers
General Information
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Disease targeted
Regulatory Information
Pathway:
MDR
Class:
Class IIb
Verified by Health AI Register
Other certifications
Not specified
Evidence & Research
Peer-Reviewed Papers
Cost-effectiveness analysis of computer aided detection for tuberculosis in Ghana: A decision-analytic modeling study
PLOS One · Aug 2026
Computer-aided detection pragmatic threshold calibration in TB active case finding: A mixed-methods study in Tondo, Manila
PLOS Global Public Health · Aug 2026
Computer-aided detection for radiological disease severity classification on chest radiograph in children with intra-thoracic tuberculosis
PLOS Global Public Health · Jun 2026
Beyond accuracy: evaluating the operational feasibility and diagnostic yield of CAD4TB vs. Timika score for scalable TB screening in low-resource settings
Frontiers in Digital Health · May 2026
PET–CT benchmarked detection and 5-year progression of asymptomatic tuberculosis: a longitudinal, prospective cohort study
The Lancet Respiratory Medicine · Mar 2026
A multi-country head-to-head accuracy comparison of automated chest x-ray algorithms for tuberculosis
Annals of the American Thoracic Society · Jan 2026
Contribution of artificial intelligence to the imaging diagnosis of pediatric pulmonary tuberculosis
Revista do Instituto de Medicina Tropical de São Paulo · Jan 2026
Routine active case finding in Nigerian penitentiary institutions: comparing yields from digital X-ray with CAD4TB and WHO 4-symptom screening
BMC Infectious Diseases · Jan 2026
Improving Tuberculosis Diagnosis Through Artificial Intelligence (CAD4TB) and Stool Xpert MTB/RIF Testing: A Prospective Study From Oromia, Ethiopia
Open Forum Infectious Diseases · Dec 2025
Impact of the use of the ultra-portable digital x-ray with CAD4TB for active case finding for tuberculosis in Nigeria
Frontiers in Digital Health · Jun 2025
Performance of CAD4TB artificial intelligence technology in TB screening programmes among the adult population in South Africa and Lesotho
Journal of Clinical Tuberculosis and Other Mycobacterial Diseases · Jun 2025
Clinical evaluation of computer-aided digital x-ray detection of pulmonary tuberculosis during community-based screening or active case-finding: a case–control study
The Lancet Global Health · Feb 2025
Comparative analysis of the impact of portable digital X-ray on TB screening in hard-to-reach areas in Nigeria
Public Health Action · Feb 2025
Diagnostic Accuracy of Chest X-ray Computer-Aided Detection Software for Detection of Prevalent and Incident Tuberculosis in Household Contacts
Clinical Infectious Diseases · Dec 2024
Breaking the threshold: Developing multivariable models using computer-aided chest X-ray analysis for tuberculosis triage
International Journal of Infectious Diseases · Sep 2024
Evaluation of C-Reactive Protein and Computer-Aided Analysis of Chest X-rays as Tuberculosis Triage Tests at Health Facilities in Lesotho and South Africa
Clinical Infectious Diseases · Aug 2024
Computer-aided detection of tuberculosis from chest radiographs in a tuberculosis prevalence survey in South Africa: external validation and modelled impacts of commercially available artificial intelligence software
The Lancet Digital Health · Jul 2024
Evaluation of a population-wide, systematic screening initiative for tuberculosis on Daru island, Western Province, Papua New Guinea
BMC Public Health · Apr 2024
Comparing different versions of computer-aided detection products when reading chest X-rays for tuberculosis
PLOS Digital Health · Jun 2022
Tuberculosis detection from chest x-rays for triaging in a high tuberculosis-burden setting: an evaluation of five artificial intelligence algorithms
The Lancet Digital Health · Aug 2021
Computer aided detection of tuberculosis on chest radiographs: An evaluation of the CAD4TB v6 system
Scientific Reports · Mar 2020
Technical Specifications
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Source: Vendor | First published: May 2, 2024 | Last updated: Sep 28, 2026