Bone AgeNCT07121283
Artificial Intelligence Assisted Bone Age Assessment
A study testing True AI and Fake AI in people with Bone Age, run by Cheng-Hsin General Hospital at 1 site in Taiwan.
Trial summary
AI-Assisted Bone Age Assessment Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Bone Age
- What is being tested?
- True AI and Fake AI
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 8 participants
- Where
- 1 siteTaiwan
- Study dates
- 1 Sep 2025to 18 Aug 2026
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Who may be able to join
- Exams read by radiologists who interpret pediatric skeletal age exams and verbally consent to participate
Who cannot join
- 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
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
About this study
Official title: Comparison of the Difference in Bone Age Readings Among Radiologists Using Artificial Intelligence
AI-Assisted Bone Age Assessment
Read the 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.
- Conditions
- Bone Age
- Being tested
- True AI, Fake AI
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
True AIDevice
True output from bone age AI
Fake AIDevice
Randomized output from bone age AI
| Study group | Role | What they receive |
|---|---|---|
| True AI | Experimental | Not described Receives: Device: True AI |
| Fake AI | Experimental | Not described Receives: Device: Fake AI |
What is being measured
The primary outcome is the main question the study is designed to answer.
Difference of Skeletal Age Estimate
Mean absolute difference of bone age assessment between true AI-assisted and fake AI-assisted among radiologists
Measured: Five months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted13 Aug 2025
- Study start1 Sep 2025
- Primary completion18 Feb 2026
- Study completion18 Aug 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Bone AgeStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Crossover
- Model description
- 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.
- Masking
- Single blind
- Who is masked
- Participant
- Enrolment
- 8 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Cheng-Hsin General Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Yen-Huai Lin, Dr., Principal investigator, Cheng-Hsin General Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07121283
- Sponsor's protocol ID
- (1141)113A-71
- Status last verified
- Apr 2026
- First submitted
- 30 Jul 2025
- Last updated
- 17 Apr 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 17 Apr 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Comparison of the Difference in Bone Age Readings Among Radiologists Using Artificial Intelligence
- ClinicalTrials.gov ID
- NCT07121283
- Acronym / sponsor ID
- (1141)113A-71
- Conditions
- Bone Age
- Study type
- Interventional
- Recruitment status
- Enrolling by invitation
- Enrolment
- 8 participants (estimated)
- Lead sponsor
- Cheng-Hsin General HospitalUniversity, hospital or other
- Study start
- 1 Sep 2025 (actual)
- Primary completion
- 18 Feb 2026 (actual)
- Study completion
- 18 Aug 2026 (estimated)
- First posted
- 13 Aug 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Crossover
- Masking
- Single blind (participant)
- Number of arms
- 2
- Model description
- 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.
| Arm | Type | Receives |
|---|---|---|
| True AI | Experimental | Device: True AI |
| Fake AI | Experimental | Device: Fake AI |
Who may qualify
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
Key inclusion criteria (1 listed)
- Exams read by radiologists who interpret pediatric skeletal age exams and verbally consent to participate
Key exclusion criteria (1 listed)
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| True AITrue output from bone age AI | Device | True AI |
| Fake AIRandomized output from bone age AI | Device | Fake AI |
Primary outcome
Difference of Skeletal Age Estimate
Time frame: Five months
Mean absolute difference of bone age assessment between true AI-assisted and fake AI-assisted among radiologists
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 17 Apr 2026.
- Individual participant dataSharing planned: No
Related trials for Bone Age
RecruitingPhase 3
A Study of MACI in Patients Aged 17 to 65 Years With Symptomatic Chondral or Osteochondral Defects of the Ankle
Chondral Defect, Articular Cartilage Defect
RecruitingPhase 1/2
Pacritinib, a Kinase Inhibitor of CSF1R, IRAK1, JAK2, and FLT3, in Adults and Pediatric Participants 12 Years of Age or Older With Myelodysplastic Syndromes or Myelodysplastic/Myeloproliferative Neoplasms
Myelodysplastic Syndromes
RecruitingPhase 2
Testing New Therapies for Patients With Acute Myeloid Leukemia Who Are Newly Diagnosed and Have Not Yet Started Treatment (A MyeloMATCH Treatment Trial)
Acute Myeloid Leukemia, Acute Myeloid Leukemia Arising From Previous Myelodysplastic/Myeloproliferative Neoplasm
Active, not recruitingPhase 2
Azacitidine and Gemtuzumab Ozogamicin in Treating Older Patients With Previously Untreated Acute Myeloid Leukemia
Acute Myeloid Leukemia, Adult Acute Megakaryoblastic Leukemia
Enrolling by invitationObservational study
Multidimensional Determinants of Functional Health In Women Aged 45-60
Healthy, Perimenopausal Depression
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Yen-Huai Lin, Dr. principal investigator
Cheng-Hsin General Hospital
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing True AI and Fake AI in people with Bone Age, run by Cheng-Hsin General Hospital at 1 site in Taiwan.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: enrolling by invitation, as of the sponsor's last update on 17 Apr 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Taiwan. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Difference of Skeletal Age Estimate (time frame: Five months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 17 Apr 2026.