Multi-agent LLMs for Decision Support in Cervical Cancer During Pregnancy

Sponsor
Obstetrics & Gynecology Hospital of Fudan University
Study ID
NCT07318701
Status
Not Yet Recruiting

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Conditions

Eligibility Criteria

Sex
FEMALE
Age
N/A - N/A
Healthy Volunteers
Not accepted

Interventions

  • multi-disciplinary agents group — OTHER
    generate diagnosis and treatment opinions for each case from multi-disciplinary agents
  • real MDT group — OTHER
    generate diagnosis and treatment opinions for each case from a real MDT team inclduing senior physicians from relevant departments, including gynecologic oncology, pediatrics, obstetrics, medical oncology and radiation oncology.
  • junor doctor group — OTHER
    generate diagnosis and treatment opinions for each case from junior doctor who are residents from relevant departments, including gynecologic oncology, pediatrics, obstetrics, medical oncology and radiation oncology.
  • junor doctor group with aid of MDT agents — OTHER
    generate diagnosis and treatment opinions for each case from junior doctor who are residents from relevant departments, including gynecologic oncology, pediatrics, obstetrics, medical oncology and radiation oncology after referring to the results from MDT agent .

Study Details

The aim of this study is to develop an AI-assisted decision-making system based on multi-agent large language models and to evaluate its effectiveness and accuracy in the diagnosis and treatment of cervical cancer during pregnancy.

Key Dates

First listed
Jan 6, 2026
Start date
Jan 1, 2026
Status verified
Jan 2026
Primary completion
Jun 30, 2026
Completion
Oct 30, 2026

Study Design

Enrollment
150 participants (estimated)
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
SUPPORTIVE_CARE

Arms

  • Experimental: Arm1: multi-disciplinary agents group
    generate diagnosis and treatment opinions from multi-disciplinary agents
  • Placebo Comparator: Arm2: real MDT group/ junior doctors group/junior doctors after referring to agent results group
    generate diagnosis and treatment opinions from real MDT group/ junior doctors group/junior doctors after referring to agent results group

Primary Outcome Measure

Accuracy of the MDT decision [ Time Frame: immediately after the intervention ]

Central Contacts

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