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Detection of abnormality in chest X-rays using deep learning

Detection of abnormality in chest X-rays using deep learning

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
TCTR
Registry ID
TCTR20200925003
Enrollment
1000
Registered
2020-09-25
Start date
2020-09-23
Completion date
Unknown
Last updated
2026-08-03

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

CXRs images with and without definite diagnosis. CXR Deep learning Detection Abnormality

Interventions

No abnormality found on CXR,Abnormal CXR incldes pulmonary and cardiac diseases.
Diagnostic,Diagnostic
No finding on CXR,Abnormal CXR

Sponsors

Faculty of Medicine, Khon Kaen University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 100 Years

Inclusion criteria

Inclusion criteria: CXR with pulmonary and cardiac diseases. CXR without abnormality.

Exclusion criteria

Exclusion criteria: No image in local PACS

Design outcomes

Primary

MeasureTime frame
Detection of abniormal CXR At the end of the project Accuracy/ ROC curve—

Secondary

MeasureTime frame
Localization of abnormality At the end of the project Accuracy/ Dice index—

Countries

Thailand

Contacts

Public ContactArunnit Boonrod

Radiology department, Faculty of Medicine, Khon Kaen University

arunsi@kku.ac.th0833687472

Outcome results

None listed

Source: TCTR (via WHO ICTRP) · Data processed: Aug 9, 2026