Clinical trial · Observational
Retrospective Study of Carebot AI CXR Performance in Preclinical Practice
Chest X-Ray Abnormality Detection Using Artificial Intelligence: Retrospective Study of Carebot AI CXR Performance in Preclinical Practice
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
The purpose of this study is to describe the design, methodology and evaluation of the preclinical test of Carebot AI CXR software, and to provide evidence that the investigated medical device meets user requirements in accordance with its intended use. Carebot AI CXR is defined as a recommendation system (classification "prediction") based on computer-aided detection. The software can be used in a preclinical deployment at a selected site before interpretation (prioritization, display of all results and heatmaps) or after interpretation (verification of findings) of CXR images, and in accordance with the manufacturer's recommendations. Given this, a retrospective study is performed to test the clinical effectiveness on existing CXRs.
Conditions
Conditions (12)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Artificial Intelligence | — | UNRESOLVED | — |
| Atelectasis | — | UNRESOLVED | — |
| Cardiomegaly | — | UNRESOLVED | — |
| Consolidation | — | UNRESOLVED | — |
| Fracture Rib | — | UNRESOLVED | — |
| Hilar Calcification | — | UNRESOLVED | — |
| Lung Cancer | Malignant Lung Neoplasm | CURATED_EXACT | 0.92 |
| Lung Diseases | — | UNRESOLVED | — |
| Pleural Effusion | — | UNRESOLVED | — |
| Pneumonia |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Carebot AI CXR | Device | — | UNRESOLVED |
Design
Arms and outcomes
Arms (1)
- label
- Retrospective collection of DICOM patient files for the period 15-17 August
- description
- To collect the CXR data for retrospective study, we addressed a municipal hospital in the Czech Republic that provides healthcare services to up to 130,000 residents of a medium-sized city (approximately 70,000 inhabitants) and the surrounding area. 127 anonymized CXR images were collected between August 15 and 17, 2022, and subsequently submitted to five independent radiologists of varying experience for annotation. The selected radiologists were asked to assess whether the CXR image shows any of the 12 abnormalities mentioned above. Pediatric CXR images (under 18 years of age), scans with technical problems (poor image quality, rotation), and images in lateral projection were excluded from the dataset.
- interventionNames
- Device: Carebot AI CXR
Primary outcomes (1)
- measure
- Primary objective
- timeFrame
- 20-10-2022
- description
- Comparison of the accuracy of radiologist and Carebot AI CXR image assessment.
Secondary outcomes (1)
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
Show eligibility criteria text
Inclusion Criteria: * Hospital patients who were referred for chest radiography between August 15 and 17, 2022. Exclusion Criteria: * Pediatric CXR images (under 18 years of age) * Scans with technical problems (poor image quality, rotation) * Images in lateral projection
References
Publications (0)
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