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Multi-Reader Retrospective Study Examining Carebot AI CXR 2.0.21-v2.01 Implementation in Everyday Radiology Clinical Practice

NCT05963945 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 956

Last updated 2023-07-27

No results posted yet for this study

Summary

The primary objective is to evaluate the performance parameters of the proposed DLAD (Carebot AI CXR) in comparison to individual radiologists.

Conditions

  • Pneumothorax
  • Pulmonary Nodule, Solitary
  • Atelectasis
  • Subcutaneous Emphysema
  • Cardiomegaly
  • Consolidation
  • Pleural Effusion

Interventions

DEVICE

Carebot AI CXR

The proposed DLAD (Carebot AI CXR) is a deep learning-based medical device designed to assist radiologists in interpreting chest X-ray images acquired in anteroposterior (AP) or posteroanterior (PA) projection. By employing advanced deep learning algorithms, this solution enables automatic detection of abnormal findings by analyzing visual patterns associated with specific conditions. The targeted abnormalities include atelectasis (ATE), consolidation (CON), pleural effusion (EFF), pulmonary lesion (LES), subcutaneous emphysema (SCE), cardiomegaly (CMG), and pneumothorax (PNO). The DLAD functions as a prediction algorithm complemented by various application peripherals, such as web-based communication tools, DICOM file conversion capabilities, and storage and reporting libraries supporting both DICOM Structured Report and DICOM Presentation State formats.

Sponsors & Collaborators

  • Carebot s.r.o.

    lead INDUSTRY

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2022-10-18
Primary Completion
2022-11-17
Completion
2023-03-21

Countries

  • Czechia

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05963945 on ClinicalTrials.gov