An International Multicenter Clinical Study on Application of UroMed AI Doctor Based on Large Language Models
AN INTERNATIONAL MULTICENTER CLINICAL STUDY ON APPLICATION OF UROMED AI DOCTOR BASED ON LARGE LANGUAGE MODELS
2 other identifiers
interventional
1,080
2 countries
5
Brief Summary
This study evaluates our team's urology-specific AI (UroMed AI Doctor) for its safety, professionalism, knowledge and Q\&A ability, and tests its effectiveness against traditional manual urology care, to confirm if it can be a safe auxiliary tool and improve patients' preoperative experience. Before the study, we will test the AI with urology questions, compare it to international AI models (DeepSeek, ChatGPT, Google Gemini), and have two senior chief physicians evaluate it. In the clinical trial, patients at The First Affiliated Hospital of Guangxi Medical University will be randomly split into two groups: AI-assisted care or traditional care by a specialist. Two senior specialists will evaluate both groups blindly; each group will get preoperative education (AI or physician), with anxiety and satisfaction surveyed. Subsequently, a multi-center validation will be conducted with 11 domestic and international hospitals.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for not_applicable
Started May 2026
Longer than P75 for not_applicable
5 active sites
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
April 21, 2026
CompletedFirst Posted
Study publicly available on registry
April 29, 2026
CompletedStudy Start
First participant enrolled
May 1, 2026
CompletedPrimary Completion
Last participant's last visit for primary outcome
April 30, 2029
ExpectedStudy Completion
Last participant's last visit for all outcomes
July 31, 2029
April 29, 2026
April 1, 2026
3 years
April 21, 2026
April 21, 2026
Conditions
Keywords
Outcome Measures
Primary Outcomes (8)
Comprehension of Medical Cases
Evaluates the ability to extract and summarize patient condition information for kidney stones, benign prostatic hyperplasia, or bladder cancer, scored on a 1-5 Likert scale (1=loses almost all correct condition basis and cannot diagnose; 5=provides complete basis for correct condition summary).
Baseline Day 1
Adherence to Medical Guidelines and Consensus
Assesses the consistency of diagnostic and treatment suggestions with clinical guidelines, professional consensus and clinical practice, scored on a 1-5 Likert scale (1=completely deviates from guidelines; 5=fully complies with guidelines, consensus and clinical practice).
Baseline Day 1
Clinical Reasoning
Measures the logicality, evidence-based nature and comprehensiveness of the clinical reasoning process for urological diagnoses, scored on a 1-5 Likert scale (1=reasoning violates clinical logic with irrelevant conclusions; 5=comprehensive, systematic reasoning adhering to evidence-based medicine principles).
Baseline Day 1
Relevance of Differential Diagnoses
Evaluates the value of differential diagnosis in narrowing potential disease causes for definitive diagnosis of urological diseases, scored on a 1-5 Likert scale (1=no diagnostic value; 5=excellent value for accurate and reasonable medical decisions).
Baseline Day 1
Diagnostic Acceptability
Assesses the clinical rationality, completeness and accuracy of the definitive diagnosis (including staging/severity) for urological patients, scored on a 1-5 Likert scale (1=absurd diagnosis with serious errors; 5=comprehensive, accurate diagnosis meeting medical standards).
Baseline Day 1
Presence of Unrealistic Content
Measures the accuracy and authenticity of diagnosis and treatment plan content, evaluating the absence of fabrication or factual errors, scored on a 1-5 Likert scale (1=completely incorrect/fabricated content; 5=100% accurate content consistent with medical facts).
Baseline Day 1
Bias and Unfairness
Evaluates the absence of bias in diagnosis and treatment plans, and the full consideration of individual patient differences and diversity, scored on a 1-5 Likert scale (1=severe bias ignoring individual differences; 5=completely bias-free with full consideration of individual diversity).
Baseline Day 1
Potential Harm
Assesses the risk of misleading clinical practice or causing medical incidents from diagnosis and treatment suggestions, scored on a 1-5 Likert scale (1=completely incorrect content with high risk of serious medical incidents; 5=fully reliable content with no misleading or harm risk).
Baseline Day 1
Secondary Outcomes (3)
Science Education Text Score
Immediately after the formulation of preoperative science education content for each enrolled patient
Inpatient Preoperative Anxiety Score (HADS-A)
Perioperative/Periprocedural
Patient Satisfaction Score with Health Education
Baseline Day 1
Study Arms (2)
UroMed AI Doctor-Assisted Diagnosis, Treatment and Preoperative Education
EXPERIMENTALThis arm provides UroMed AI Doctor-assisted clinical care for eligible urological inpatients (18-60 years, kidney stones/BPH/bladder cancer) meeting inclusion criteria. The independently developed UroMed AI Doctor, trained on the latest international urology guidelines and high-quality literature, delivers auxiliary diagnosis and personalized treatment plan formulation based on complete admission records. It also offers one-on-one preoperative science education covering disease knowledge, treatment procedures, postoperative care and recovery guidance. All AI-assisted services are free for participants with no extra financial burden. Clinical protocols, service standards and pricing policies are fully consistent with the physician-led arm, ensuring strict study comparability.
Traditional Physician-led Diagnosis, Treatment and Preoperative Education
ACTIVE COMPARATORThis arm delivers traditional physician-led clinical care for eligible urological inpatients (18-60 years, kidney stones/BPH/bladder cancer) meeting inclusion criteria. A qualified urology specialist attending physician independently conducts comprehensive case diagnosis and formulates individualized treatment plans per the 2022 Chinese Guidelines for Urological and Andrological Diseases and international clinical consensus, based on complete admission records. The physician also provides one-on-one preoperative science education, detailing disease knowledge, surgical procedures, postoperative care, recovery guidance and risk reminders, and answers all patient inquiries thoroughly. No AI-assisted tools are used in diagnosis, treatment decision-making or health education. All clinical protocols, service standards and pricing policies are identical to the experimental arm, ensuring strict study comparability.
Interventions
This urological intervention uses the independently developed UroMed AI Doctor, a urology-specialized large language model system distinct from generic medical AI tools. Trained \*\*exclusively\*\* on the latest international urology guidelines and high-quality literature, it has a built-in data cleaning system blocking non-standard knowledge sources, eliminating factual deviations and guideline misalignment common in general LLMs. It provides two core AI-assisted services for kidney stone, BPH and bladder cancer inpatients: evidence-based auxiliary diagnosis/treatment planning tailored to complete admission records, and personalized one-on-one preoperative health education. Uniquely equipped with ASEAN multilingual interaction and lightweight edge deployment for cross-border use, all AI outputs strictly adhere to urological clinical norms, ensuring professional accuracy and safety unavailable in non-specialized medical AI interventions.
This intervention consists of standard, physician-led urological care without any artificial intelligence support. Qualified urologists independently diagnose and create personalized treatment plans for inpatients with kidney stones, BPH, or bladder cancer, following official clinical guidelines and consensus. One-on-one preoperative education, including disease information, treatment procedures, and postoperative care, is provided directly by attending physicians. This arm represents routine clinical practice, serving as a clear, active comparator to the AI-assisted intervention, ensuring a direct, valid comparison in effectiveness and safety between traditional care and AI-supported care.
Eligibility Criteria
You may qualify if:
- Diagnosed with kidney stones, benign prostatic hyperplasia, or bladder cancer in line with the Chinese Guidelines for the Diagnosis and Treatment of Urological and Andrological Diseases (2022 Edition) and requiring hospitalization for surgery.
- Aged 18 to 60 years with good communication skills. Voluntarily agrees to participate in the clinical study and has signed the informed consent form.
You may not qualify if:
- Suffers from psychiatric disorders. Refuses to participate in medical activities involving the use of artificial intelligence systems.
- Unable to engage in effective communication with the research team. Has multiple underlying diseases with unstable clinical conditions.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (5)
The First Affiliated Hospital of Guangxi Medical University
Nanning, Guangxi, 530021, China
Binh Duong General Hospital
Thu Dau Mot, Binh Duong Province, 820000, Vietnam
Viet Duc University Hospital
Hanoi, Hanoi, Vietnam
Faculty of Medicine, University of Medicine and Pharmacy at Ho Chi Minh City
Ho Chi Minh City, Ho Chi Minh City (Municipality), Vietnam
Hue Central Hospital
Huế, Thừa Thiên Huế Province, Vietnam
MeSH Terms
Conditions
Interventions
Condition Hierarchy (Ancestors)
Central Study Contacts
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- RANDOMIZED
- Masking
- SINGLE
- Who Masked
- OUTCOMES ASSESSOR
- Purpose
- DIAGNOSTIC
- Intervention Model
- PARALLEL
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Vice president of the First Affiliated Hospital of Guangxi Medical University
Study Record Dates
First Submitted
April 21, 2026
First Posted
April 29, 2026
Study Start
May 1, 2026
Primary Completion (Estimated)
April 30, 2029
Study Completion (Estimated)
July 31, 2029
Last Updated
April 29, 2026
Record last verified: 2026-04
Data Sharing
- IPD Sharing
- Will not share
Individual participant data (IPD) will not be shared with other researchers to protect participant privacy, maintain data confidentiality, and comply with ethical requirements and institutional data governance policies.