Trial of Artificial Intelligence for Chest Radiography

NCT ID: NCT06456203

Last Updated: 2024-06-13

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

NOT_YET_RECRUITING

Clinical Phase

NA

Total Enrollment

10000 participants

Study Classification

INTERVENTIONAL

Study Start Date

2024-10-31

Study Completion Date

2025-12-31

Brief Summary

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Randomized Clinical Trial of the impact of Chest radiograph AI-assisted triage and report generation upon clinical outcomes and an economic analysis of impact of AI decision support on radiology service delivery.

Detailed Description

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Randomized, prospective selection of patients. Control group involves radiologists reporting chest radiographs as per reference standard clinical workflow Intervention group involves radiologists assisted with AI reporting an AI-triaged worklist of chest radiographs using an AI report generation tool Clinical outcomes on patients are studied at pre-determined study endpoints, including time to discharge from the hospital and re-admission rates.

Economic analysis on cost-avoidance from man-hours saved from report generation and triage.

Conditions

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Pneumonia Lung Cancer

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

DIAGNOSTIC

Blinding Strategy

NONE

Study Groups

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Control Arm

Chest radiographs reported with AI assistance

Group Type NO_INTERVENTION

No interventions assigned to this group

AI assisted

AI assisted detection, triage and reporting of CXR

Group Type ACTIVE_COMPARATOR

AI

Intervention Type DIAGNOSTIC_TEST

Artificial intelligence triage and reporting system

Interventions

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AI

Artificial intelligence triage and reporting system

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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Inclusion Criteria

* All patients attending radiography to have chest radiographs during the study period

Exclusion Criteria

* age below 14
* deceased before discharge
* chest radiograph performed in non-standard projections
Minimum Eligible Age

14 Years

Maximum Eligible Age

130 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Duke-NUS Graduate Medical School

OTHER

Sponsor Role lead

Responsible Party

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Charlene Liew

Clinical Assistant Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Other Identifiers

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2023/2280

Identifier Type: -

Identifier Source: org_study_id

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