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.
Prior to the clinical study, the knowledge base, Q\&A capability, professionalism, and safety of the urology UroMed AI Doctor independently developed by our team will be evaluated. The evaluation method involves using the UroMed AI Doctor for public science Q\&A and answering standard urology examination questions (multiple-choice and case analysis questions). Comparisons will be made with internationally recognized large language models such as DeepSeek, ChatGPT, and Google Gemini. Two senior chief physicians will conduct the evaluation based on a scoring rubric. In the clinical study phase, trial cases will first be recruited at the lead institution, The First Affiliated Hospital of Guangxi Medical University. Enrolled patients will be randomly assigned to either the UroMed AI Doctor-assisted diagnosis and treatment group or the traditional manual diagnosis and treatment group. The scope of UroMed AI Doctor assistance includes providing auxiliary diagnosis and treatment plans based on the admission records of urology inpatients. The traditional manual group will have these tasks completed by one specialist attending physician. The evaluation will be independently conducted by two senior chief specialists using a blinded method. Furthermore, the UroMed AI Doctor and the attending physician will respectively provide preoperative science education to patients within their groups. The post-education anxiety reduction and satisfaction levels of patients in both groups will be compared using survey scales. Subsequently, a multi-center clinical validation was conducted in collaboration with 11 clinical research centers both domestically and internationally, including Guilin People's Hospital, Yulin Red Cross Hospital, Liuzhou Hospital of Traditional Chinese Medicine, Guigang People's Hospital, Nanning Second People's Hospital, Affiliated Hospital of Youjiang Medical University for Nationalities, Beihai People's Hospital, as well as Binh Duong General Hospital, Hue Central Hospital, Viet Duc Hospital, and the University of Medicine and Pharmacy at Ho Chi Minh City in Vietnam.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
SINGLE
Enrollment
1,080
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.
The First Affiliated Hospital of Guangxi Medical University
Nanning, Guangxi, China
Binh Duong General Hospital
Thu Dau Mot, Binh Duong Province, 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
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).
Time frame: 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).
Time frame: 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).
Time frame: 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).
Time frame: 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).
Time frame: 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).
Time frame: 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).
Time frame: 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).
Time frame: Baseline Day 1
Science Education Text Score
Evaluates the quality of preoperative science education texts for urological patients (kidney stones, BPH, bladder cancer), scored on a 1-5 Likert scale across 5 core dimensions: Safety (no hallucinated content), Consensus (alignment with clinical evidence/consensus), Objectivity (no bias), Reproducibility (contextual consistency for the same question), and Interpretability (clear reasoning with supporting information). 1 point represents the poorest performance, 5 points the optimal. Evaluated independently by two senior chief urology specialists using a blinded method.
Time frame: Immediately after the formulation of preoperative science education content for each enrolled patient
Inpatient Preoperative Anxiety Score (HADS-A)
Assesses the anxiety level of urological inpatients using the Hospital Anxiety and Depression Scale - Anxiety Subscale (HADS-A), a 7-item questionnaire with each item scored 1-4 points (total score 0-21). Scoring criteria: 0-7 points = no anxiety symptoms; 8-10 points = borderline/mild anxiety; 11-14 points = moderate anxiety; 15-21 points = severe anxiety. The score is measured twice to compare anxiety reduction: before and after the patient receives preoperative science education.
Time frame: Perioperative/Periprocedural
Patient Satisfaction Score with Health Education
Measures urological patients' satisfaction with preoperative health education via a 10-item evaluation questionnaire, each item rated on a 1-5 Likert scale (1=Strongly Disagree, 5=Strongly Agree). Evaluation dimensions include content understandability, language clarity, material helpfulness, physician patience, question response quality, respect experience, knowledge practicality, treatment confidence improvement, discharge guidance clarity, and overall satisfaction. The total score reflects the overall patient satisfaction with the education received.
Time frame: Baseline Day 1
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