Artificial Intelligence Assisted Bone Age Assessment
- Conditions
- Bone Age
- Registration Number
- NCT07121283
- Lead Sponsor
- Cheng-Hsin General Hospital
- Brief Summary
AI-Assisted Bone Age Assessment
- Detailed Description
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.
Recruitment & Eligibility
- Status
- ENROLLING_BY_INVITATION
- Sex
- All
- Target Recruitment
- 8
- Exams read by radiologists who interpret pediatric skeletal age exams and verbally consent to participate
- Exams containing more than one radiograph will not be included. No further exclusion criteria will be applied on the basis of image quality metrics or manufacturers
Study & Design
- Study Type
- INTERVENTIONAL
- Study Design
- CROSSOVER
- Primary Outcome Measures
Name Time Method Difference of Skeletal Age Estimate Five months Mean absolute difference of bone age assessment between true AI-assisted and fake AI-assisted among radiologists
- Secondary Outcome Measures
Name Time Method
Trial Locations
- Locations (1)
Cheng Hsin General Hospital
🇨🇳Taipei, Taiwan
Cheng Hsin General Hospital🇨🇳Taipei, Taiwan