Development of an AI-Agent for Urological Disease Diagnosis and Treatment | NCT07721935

NCT07721935

Overview

NCT ID: NCT07721935
Lead Sponsor: Sun Yat-Sen Memorial Hospital of Sun Yat-Sen UniversityOTHER
Official Title: Development of an AI-Agent for Diagnosis and Treatment of Urological Diseases
Brief Summary: Urological diseases such as urinary stones, prostate cancer, and bladder cancer are very common and often require highly specialized diagnosis and treatment. Today, the quality of care can vary between doctors, and there are not enough urology specialists to meet patient demand. Artificial intelligence (AI) may help doctors make faster and more consistent decisions.

This study aims to develop and test an AI-powered assistant called "UroAgent" that supports doctors in diagnosing and treating urological diseases. UroAgent is built on a large language model trained specifically for urology and is connected to tools that help it retrieve medical knowledge and analyze images. To build and test UroAgent, the research team will use 1,500 past patient records from 2010-2025 and collect 500 new patient cases for validation, for a total of 2,000 cases. This is an observational study: no patient's medical treatment will be changed because of it. The goal is to create a reliable AI tool that helps improve urological care for patients.

Status and Timeline

Status: Recruiting
Last Update Posted: Jul 23, 2026Actual
Start Date: Apr 1, 2025Actual
Primary Completion Date: Dec 31, 2026Estimated
Completion Date

Participation Criteria

Ages Eligible for Study: Child (0-17)Adult (18-64)Older Adult (65+)
Sexes Eligible for Study: All
Accepts Healthy Volunteers?: No
Eligibility Criteria: Inclusion Criteria:

Diagnosed with a urological disease (e.g., urinary stones, prostate cancer, bladder cancer, and other urological conditions).

Availability of complete clinical information, imaging data, and surgical video required for model development and validation.

Exclusion Criteria:

1. Missing clinical information, imaging data, or surgical video.

Study Plan

Study Type: Observational
Phase: No data available
Enrollment: 2,000Estimated
Primary Purpose: No data available
Allocation: No data available
Interventional Model: No data available
Masking: No data available

Contacts and Locations

Central Contacts: Mingzhou DaiContact
daimzh3@mail2.sysu.edu.cn+86 19924684262

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Participant Group/Arms

Urological Disease Cohort

The cohort consists of patients diagnosed with urological diseases-including urinary stones, prostate cancer, and bladder cancer-at Sun Yat-sen Memorial Hospital. A total of 2,000 cases are included: 1,500 retrospective cases recorded between 2010 and 2025 (used for model development) and 500 prospectively and consecutively enrolled cases (used for independent validation); all records are de-identified. The intervention (technology) of interest is "UroAgent," an artificial-intelligence diagnostic-and-treatment agent built on a urology-specialized large language model with integrated tool modules (knowledge retrieval, image interpretation). For each case, UroAgent's diagnostic and treatment recommendations are generated and compared with the analyses provided by human urology specialists, to evaluate the agent's performance-diagnostic accuracy, recommendation appropriateness, completeness, and safety-against expert judgment.