Artificial Intelligence Assisted Bone Age Assessment

NCT ID: NCT07121283

Last Updated: 2025-08-13

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

ENROLLING_BY_INVITATION

Clinical Phase

NA

Total Enrollment

8 participants

Study Classification

INTERVENTIONAL

Study Start Date

2025-09-01

Study Completion Date

2026-02-18

Brief Summary

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AI-Assisted Bone Age Assessment

Detailed Description

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Artificial intelligence (AI) has gained great advancement in the application in clinical practice. However, this might introduce the automation bias, that the clinician over-rely on the incorrect advise from AI. The automation bias could have a great impact on the clinical decisions in an AI era. However, efforts to mitigate the automation bias tend to focus on upgrading AI performance and reducing bias in algorithms, which neglect the role of users. The aim of this study is to investigates the impact of the automation bias on the bone age assessment among radiologists with different seniority.

Conditions

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Bone Age

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

CROSSOVER

Six radiologists with different seniority (senior, intermediate, and junior) were recruited. The 200 standard films were evenly divided into two subsets: datasets A and B. A randomized crossover design with four periods (each with a 4-week duration) was arranged to minimize anticipation and carryover effects. Each radiologist who made an assessment with the aid of true AI or fake AI information could agree or disagree with the AI's predictions. The information of the fake AI was resulted from the randomization of the outputs from the true AI. Each radiologist was blinded to the existence of the fake AI.
Primary Study Purpose

DIAGNOSTIC

Blinding Strategy

SINGLE

Participants

Study Groups

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True AI

Group Type EXPERIMENTAL

True AI

Intervention Type DEVICE

True output from bone age AI

Fake AI

Group Type EXPERIMENTAL

Fake AI

Intervention Type DEVICE

Randomized output from bone age AI

Interventions

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True AI

True output from bone age AI

Intervention Type DEVICE

Fake AI

Randomized output from bone age AI

Intervention Type DEVICE

Eligibility Criteria

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Inclusion Criteria

* Exams read by radiologists who interpret pediatric skeletal age exams and verbally consent to participate
Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Cheng-Hsin General Hospital

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Yen-Huai Lin, Dr.

Role: PRINCIPAL_INVESTIGATOR

Cheng-Hsin General Hospital

Locations

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Cheng Hsin General Hospital

Taipei, Taiwan, Taiwan

Site Status

Countries

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Taiwan

Other Identifiers

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(1141)113A-71

Identifier Type: -

Identifier Source: org_study_id

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