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Artificial Intelligence to Improve Physicians' Interpretation of Chest X-Rays in Breathless Patients

NCT05117320 · Status: UNKNOWN · Phase: NA · Type: INTERVENTIONAL · Enrollment: 33

Last updated 2022-01-11

No results posted yet for this study

Summary

Identifying the cause of breathlessness in acute patients in the emergency department is critical and challenging. The chest X-ray is central but challenging to read for non-radiologist physicians. Often the physicians read the CXR alone due to off-hours and shortage of radiology specialists. Artificial Intelligence (AI) has the potential to aid the reading of chest X-rays. The hypothesis is that AI applied to chest X-rays improves emergency physicians' diagnostic accuracy in acute breathless patients.

Conditions

Interventions

DEVICE

AI support

Images were allocated to participants. In randomized allocation, one half of the images for each participant are viewed with AI support and the other half is viewed without AI support on the first trial day. On the second trial day the same images are viewed without versus with AI, respectively. This ensures that all images are read twice by the same participant both with and without AI support.

Sponsors & Collaborators

  • Enlitic.com

    collaborator UNKNOWN

  • Oxipit.ai

    collaborator UNKNOWN

  • Bispebjerg Hospital

    lead OTHER

Study Design

Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
NONE
Model
CROSSOVER

Eligibility

Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2021-10-19
Primary Completion
2022-02-28
Completion
2022-07-31

Countries

  • Denmark

Study Locations

More Related Trials

Entities

Diseases

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 NCT05117320 on ClinicalTrials.gov