UMIN-CTR Clinical Trial
| Unique ID issued by UMIN | UMIN000058851 |
|---|---|
| Receipt number | R000067299 |
| Scientific Title | Evaluation the Accuracy of Generative AI in Diagnosing Rare and Complex Pediatric Cases: A Retrospective Comparative Study |
| Date of disclosure of the study information | 2025/08/20 |
| Last modified on | 2025/08/20 16:45:54 |
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Basic information
Public title
Evaluation the Accuracy of Generative AI in Diagnosing Rare and Complex Pediatric Cases: A Retrospective Comparative Study
Acronym
Evaluation the Accuracy of Generative AI in Diagnosing Rare and Complex Pediatric Cases
Scientific Title
Evaluation the Accuracy of Generative AI in Diagnosing Rare and Complex Pediatric Cases: A Retrospective Comparative Study
Scientific Title:Acronym
Evaluation the Accuracy of Generative AI in Diagnosing Rare and Complex Pediatric Cases
Region
| Asia(except Japan) |
Condition
Condition
rare and complex pediatric diseases
Classification by specialty
| Pediatrics |
Classification by malignancy
Others
Genomic information
NO
Objectives
Narrative objectives1
To evaluate the diagnostic accuracy and clinical applicability of advanced generative AI models in rare and complex pediatric cases, using expert-verified historical diagnoses as the benchmark.
Basic objectives2
Efficacy
Basic objectives -Others
Trial characteristics_1
Trial characteristics_2
Developmental phase
Assessment
Primary outcomes
Diagnostic accuracy for the top three differential diagnoses generated by ChatGPT
Key secondary outcomes
Base
Study type
Observational
Study design
Basic design
Randomization
Randomization unit
Blinding
Control
Stratification
Dynamic allocation
Institution consideration
Blocking
Concealment
Intervention
No. of arms
Purpose of intervention
Type of intervention
Interventions/Control_1
Interventions/Control_2
Interventions/Control_3
Interventions/Control_4
Interventions/Control_5
Interventions/Control_6
Interventions/Control_7
Interventions/Control_8
Interventions/Control_9
Interventions/Control_10
Eligibility
Age-lower limit
| Not applicable |
Age-upper limit
| 18 | years-old | >= |
Gender
Male and Female
Key inclusion criteria
Patients aged 0 to 18 years at the time of diagnosis
Diagnoses confirmed through, diagnostic testing, or specialist evaluation
Conditions classified as rare (affecting fewer than 1 in 2,000 individuals) or complex, involving multisystem involvement or requiring specialized, coordinated care
Key exclusion criteria
Incomplete or ambiguous records
Cases lacking definitive diagnostic confirmation
Conditions that are common, self-limiting, or routinely managed in primary care settings
Target sample size
50
Research contact person
Name of lead principal investigator
| 1st name | Rahel |
| Middle name | Farhad |
| Last name | Ali |
Organization
kurdistan technical institute
Division name
Clinical Pharmacist
Zip code
NA
Address
Sulaimani Heights, Dabashan Road,Sulaymaniyah, Kurdistan, Iraq
TEL
+964-771-702-8282
rahel.ali@kti.edu.iq
Public contact
Name of contact person
| 1st name | Rahel |
| Middle name | Farhad |
| Last name | Ali |
Organization
kurdistan technical institute
Division name
Clinical Pharmacist
Zip code
NA
Address
Sulaimani Heights, Dabashan Road,Sulaymaniyah, Kurdistan, Iraq
TEL
+964-771-702-8282
Homepage URL
rahel.ali@kti.edu.iq
Sponsor or person
Institute
kurdistan technical institute
Institute
Department
Personal name
Funding Source
Organization
kurdistan technical institute
Organization
Division
Category of Funding Organization
Outside Japan
Nationality of Funding Organization
Other related organizations
Co-sponsor
Name of secondary funder(s)
IRB Contact (For public release)
Organization
University of Sulaimani
Address
H9G5+HX7, Sulaymaniyah, Sulaymaniyah Governorate, Iraq
Tel
+964 748 060 6226
NA
Secondary IDs
Secondary IDs
YES
Study ID_1
156
Org. issuing International ID_1
Ethics Committee, College of Medicine, University of Sulaimani
Study ID_2
Org. issuing International ID_2
IND to MHLW
Institutions
Institutions
Other administrative information
Date of disclosure of the study information
| 2025 | Year | 08 | Month | 20 | Day |
Related information
URL releasing protocol
Publication of results
Unpublished
Result
URL related to results and publications
Number of participants that the trial has enrolled
Results
Results date posted
Results Delayed
Results Delay Reason
Date of the first journal publication of results
Baseline Characteristics
Participant flow
Adverse events
Outcome measures
Plan to share IPD
IPD sharing Plan description
Progress
Recruitment status
Preinitiation
Date of protocol fixation
| 2025 | Year | 08 | Month | 17 | Day |
Date of IRB
Anticipated trial start date
| 2025 | Year | 12 | Month | 01 | Day |
Last follow-up date
| 2025 | Year | 12 | Month | 01 | Day |
Date of closure to data entry
Date trial data considered complete
Date analysis concluded
Other
Other related information
This retrospective, observational study will use anonymized clinical records of pediatric patients diagnosed with rare and complex conditions over the past 5 years at a tertiary hospital (Jamal Ahmad Rashid Pediatric Teaching Hospital). A 5-year timeframe was selected to ensure consistency in diagnostic standards and medical record quality.
Selected cases will be converted into structured clinical vignettes and presented to a generative AI model (e.g., GPT-4).
Management information
Registered date
| 2025 | Year | 08 | Month | 20 | Day |
Last modified on
| 2025 | Year | 08 | Month | 20 | Day |
Link to view the page
Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000067299
