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Recruiting NCT07505862

NCT07505862 Scientific Validity Assessment and Optimization of AI-Generated A3/A4 Type Questions for the Chinese Medical Licensing Examination

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Clinical Trial Summary
NCT ID NCT07505862
Status Recruiting
Phase
Sponsor Guangdong Provincial People's Hospital
Condition AI (Artificial Intelligence)
Study Type OBSERVATIONAL
Enrollment 20 participants
Start Date 2025-10-01
Primary Completion 2026-03-30

Eligibility & Interventions

Sex All sexes
Min Age 18 Years
Max Age 60 Years
Study Type OBSERVATIONAL

Eligibility Fast-Check

Enter your details for a quick preliminary check. This does not replace medical advice.

What to Expect as a Participant

This is an observational study. You will not receive an experimental treatment; researchers will collect data based on your existing condition or standard treatment.

This trial targets 20 participants in total. It began in 2025-10-01 with a primary completion date of 2026-03-30.

⚠ This information is for research awareness only. Always consult your physician before joining any clinical trial. Participation is voluntary and you may withdraw at any time.

Brief Summary

This is a cross-sectional study that primarily employs quantitative analysis, supplemented by qualitative assessment. The research is conducted in two stages: Phase I consists of a model performance comparison experiment, and Phase II involves an item quality evaluation experiment. The entire study adheres to the principles of single-blinding, randomization, and standardization to ensure scientific rigor and reproducibility. The single-blind design is implemented during the "standardized testing" phase, where the system intersperses AI-generated items with those authored by human experts. Participants remain blinded to the source of each item (AI-generated vs. human-authored) throughout the testing and scoring processes, thereby ensuring the objectivity of the evaluation results.

Eligibility Criteria

Inclusion Criteria: * 1.Professional Status: Medical students currently enrolled in a Standardized Residency Training (SRT) program. 2.Educational Background: Holders of a Bachelor of Medicine degree or higher, with foundational clinical knowledge. 3.Informed Consent: Voluntarily participate in the study and provide written informed consent. 4.Technical Competency: Proficient in using digital platforms to complete assessments and scoring. Exclusion Criteria: * 1.Conflict of Interest: Individuals involved in the AI model training, prompt engineering, or the creation of the human-authored question bank for this study. 2.Inability to Complete: Presence of visual/auditory impairments or severe illness that precludes completion of the assessment within the specified time. 3.Investigator's Discretion: Any other condition that, in the opinion of the investigator, renders the participant unsuitable for the study.

Contact & Investigator

Central Contact

Zhuoyi Chen MD

✉ 18737552662@163.com

📞 +86 18737552662

Frequently Asked Questions

Who can join the NCT07505862 clinical trial?

This trial is open to participants of all sexes, aged 18 Years or older, up to 60 Years, studying AI (Artificial Intelligence). Full inclusion and exclusion criteria are listed in the Eligibility Criteria section. Always confirm your eligibility with the research team before applying.

Is NCT07505862 currently recruiting?

Yes, NCT07505862 is actively recruiting participants. Contact the research team at 18737552662@163.com for enrollment information.

Where is the NCT07505862 trial being conducted?

This trial is being conducted at Guangzhou, China.

Who is sponsoring the NCT07505862 clinical trial?

NCT07505862 is sponsored by Guangdong Provincial People's Hospital. The trial plans to enroll 20 participants.

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ClinicalMetric — Independent clinical trial intelligence platform. Not affiliated with NIH, ClinicalTrials.gov, the U.S. FDA, or any pharmaceutical company, hospital, or clinical research organization. Trial data is sourced from ClinicalTrials.gov for informational purposes only and does not constitute medical advice. Do not make any treatment, enrollment, or health decisions based solely on information found here — always consult a qualified healthcare professional. Full Disclaimer  ·  Last Reviewed: July 2026  ·  Data Methodology