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Development of an AI-Agent for Diagnosis and Treatment of Urological Diseases

Status: Recruiting
Location: See all (3) locations...
Study Type: Observational
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.

Eligibility
Participation Requirements
Sex: All
Healthy Volunteers: f
View:

• 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.

Locations
Other Locations
China
Ganzhou People's Hospital
RECRUITING
Ganzhou
Sun Yat-sen Memorial Hospital, Sun Yat-sen University
RECRUITING
Guangzhou
Shenshan Medical Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University
RECRUITING
Shantou
Contact Information
Primary
Mingzhou Dai
daimzh3@mail2.sysu.edu.cn
+86 19924684262
Time Frame
Start Date: 2025-04-01
Estimated Completion Date: 2027-06-30
Participants
Target number of participants: 2000
Treatments
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.
Related Therapeutic Areas
Sponsors
Collaborators: Ganzhou City People's Hospital
Leads: Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

This content was sourced from clinicaltrials.gov