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

18 de julho de 2026 atualizado por: Xu Kewei, Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

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

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.

Visão geral do estudo

Status

Recrutamento

Condições

Descrição detalhada

This study protocol describes an observational study aiming to develop and validate UroAgent, an artificial-intelligence agent for the diagnosis and treatment of urological diseases. A total of 2,000 urological disease cases will be collected, comprising 1,500 retrospective cases recorded at the center between 2010 and 2025 for model development and 500 prospectively enrolled cases for independent performance validation. The primary evaluation is the concordance between UroAgent's diagnostic and treatment recommendations and the reference standards established by senior urologists, assessed through diagnostic accuracy, recommendation appropriateness, completeness, and safety; secondary evaluations include the agent's performance across disease subtypes (urinary stones, prostate cancer, bladder cancer) and its image-interpretation capability. All records will undergo de-identification, and the study will adhere to rigorous ethical standards and a pre-specified statistical analysis plan to provide robust evidence for the clinical application of this urology-specific AI agent.

Tipo de estudo

Observacional

Inscrição (Estimado)

2000

Contactos e Locais

Esta seção fornece os detalhes de contato para aqueles que conduzem o estudo e informações sobre onde este estudo está sendo realizado.

Contato de estudo

Locais de estudo

    • Guangdong
      • Guangzhou, Guangdong, China, 510000
        • Recrutamento
        • Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University
        • Contato:
      • Shantou, Guangdong, China, 516600
        • Recrutamento
        • Shenshan Medical Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University
        • Contato:
    • Jiangxi
      • Ganzhou, Jiangxi, China, 341000
        • Recrutamento
        • Ganzhou People's Hospital
        • Contato:

Critérios de participação

Os pesquisadores procuram pessoas que se encaixem em uma determinada descrição, chamada de critérios de elegibilidade. Alguns exemplos desses critérios são a condição geral de saúde de uma pessoa ou tratamentos anteriores.

Critérios de elegibilidade

Idades elegíveis para estudo

  • Filho
  • Adulto
  • Adulto mais velho

Aceita Voluntários Saudáveis

Não

Método de amostragem

Amostra Não Probabilística

População do estudo

The study population comprises patients diagnosed with urological diseases at Sun Yat-sen Memorial Hospital, including urinary stones, prostate cancer, bladder cancer, and other urological conditions. A total of 2,000 participants (cases) will be included: 1,500 retrospective cases with records from 2010 to 2025, and 500 prospective, consecutively enrolled cases. Both sexes are eligible, and the population is predominantly adult (the protocol does not specify an age cutoff; an age criterion of ≥18 years is recommended for registry entry, per the note in section 16). All included participants have complete clinical information, imaging data, and surgical video available for model development and validation. Records are de-identified prior to use. The population reflects the real-world case mix of a tertiary urology center.

Descrição

Inclusion Criteria:

  1. Diagnosed with a urological disease (e.g., urinary stones, prostate cancer, bladder cancer, and other urological conditions).
  2. 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.

Plano de estudo

Esta seção fornece detalhes do plano de estudo, incluindo como o estudo é projetado e o que o estudo está medindo.

Como o estudo é projetado?

Detalhes do projeto

Coortes e Intervenções

Grupo / Coorte
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.

O que o estudo está medindo?

Medidas de resultados primários

Medida de resultado
Descrição da medida
Prazo
Diagnostic Accuracy of UroAgent
Prazo: Retrospective cases - at data extraction (single time point); Prospective cases - at enrollment (single time point); no longitudinal follow-up.
The primary outcome is UroAgent's diagnostic accuracy, measured as the F1 score of its leading diagnosis against the reference-standard final diagnosis. The reference standard is established by senior urologists from pathology, imaging, and clinical course. F1 = 2 × Precision × Recall / (Precision + Recall), computed per case and aggregated as macro-F1 across the 2,000-case cohort (1,500 retrospective + 500 prospective). Unit of measure: F1 score (range 0-1).
Retrospective cases - at data extraction (single time point); Prospective cases - at enrollment (single time point); no longitudinal follow-up.

Medidas de resultados secundários

Medida de resultado
Descrição da medida
Prazo
Expert Subjective Accuracy Rating
Prazo: Retrospective cases - at data extraction (single time point); Prospective cases - at enrollment (single time point); no longitudinal follow-up.
Independent urologists rate the accuracy of UroAgent's diagnosis on a 5-point Likert scale (1 = completely inaccurate, 5 = completely accurate), blinded to model identity. Reported as the mean rating and the percentage of cases rated ≥ 4; disagreements resolved by a third urologist. Unit of measure: mean rating (1-5) and percentage of cases rated accurate (%).
Retrospective cases - at data extraction (single time point); Prospective cases - at enrollment (single time point); no longitudinal follow-up.
Treatment Recommendation Appropriateness of UroAgent
Prazo: Retrospective cases - at data extraction (single time point); Prospective cases - at enrollment (single time point); no longitudinal follow-up.
The proportion of cases in which UroAgent's management recommendation is rated appropriate. Two independent urologists rate each recommendation on a 5-point Likert appropriateness scale (1 = completely inappropriate, 5 = completely appropriate), blinded; "appropriate" defined as Likert ≥ 4; disagreement resolved by a third urologist. Unit of measure: percentage of cases (%) rated appropriate.
Retrospective cases - at data extraction (single time point); Prospective cases - at enrollment (single time point); no longitudinal follow-up.
Clinical Safety of UroAgent Recommendations
Prazo: Retrospective cases - at data extraction (single time point); Prospective cases - at enrollment (single time point); no longitudinal follow-up.
The rate of clinically unsafe recommendations. Each case is reviewed by senior urologists using a safety rubric and flagged (binary per case) for any contraindicated, erroneous, or potentially harmful recommendation. Unit of measure: percentage of cases (%) with ≥ 1 unsafe recommendation.
Retrospective cases - at data extraction (single time point); Prospective cases - at enrollment (single time point); no longitudinal follow-up.
Concordance and Non-Inferiority of UroAgent versus Clinician Diagnoses
Prazo: Retrospective cases - at data extraction (single time point); Prospective cases - at enrollment (single time point); no longitudinal follow-up.
On the same cases, UroAgent's diagnoses are compared with those of practicing urologists. Reported as the agreement rate (%) between UroAgent and clinician diagnoses, plus the diagnostic-accuracy difference in percentage points (pp); Cohen's κ reported as a supplementary statistic. Both are assessed against the reference-standard final diagnosis. Unit of measure: agreement rate (%) and accuracy difference (pp).
Retrospective cases - at data extraction (single time point); Prospective cases - at enrollment (single time point); no longitudinal follow-up.

Colaboradores e Investigadores

É aqui que você encontrará pessoas e organizações envolvidas com este estudo.

Patrocinador

Colaboradores

Datas de registro do estudo

Essas datas acompanham o progresso do registro do estudo e os envios de resumo dos resultados para ClinicalTrials.gov. Os registros do estudo e os resultados relatados são revisados ​​pela National Library of Medicine (NLM) para garantir que atendam aos padrões específicos de controle de qualidade antes de serem publicados no site público.

Datas Principais do Estudo

Início do estudo (Real)

1 de abril de 2025

Conclusão Primária (Estimado)

31 de dezembro de 2026

Conclusão do estudo (Estimado)

30 de junho de 2027

Datas de inscrição no estudo

Enviado pela primeira vez

12 de julho de 2026

Enviado pela primeira vez que atendeu aos critérios de CQ

18 de julho de 2026

Primeira postagem (Real)

23 de julho de 2026

Atualizações de registro de estudo

Última Atualização Postada (Real)

23 de julho de 2026

Última atualização enviada que atendeu aos critérios de controle de qualidade

18 de julho de 2026

Última verificação

1 de julho de 2026

Mais Informações

Termos relacionados a este estudo

Outros números de identificação do estudo

  • SYSKY-2025-151-03

Plano para dados de participantes individuais (IPD)

Planeja compartilhar dados de participantes individuais (IPD)?

NÃO

Descrição do plano IPD

Individual participant data (IPD) will not be shared. This single-center observational study uses de-identified clinical records, imaging, and surgical video. The retrospective cases (2010-2025) were not collected with consent for external data sharing, and applicable personal-information protection regulations (e.g., China's Personal Information Protection Law) together with institutional policy prohibit transfer of patient-level data outside the sponsoring hospital. The study's primary deliverable is the UroAgent model and aggregated performance results, which will be disseminated through peer-reviewed publications and the trial registry record. Collaboration requests will be considered case-by-case under institutional approval.

Informações sobre medicamentos e dispositivos, documentos de estudo

Estuda um medicamento regulamentado pela FDA dos EUA

Não

Estuda um produto de dispositivo regulamentado pela FDA dos EUA

Não

Essas informações foram obtidas diretamente do site clinicaltrials.gov sem nenhuma alteração. Se você tiver alguma solicitação para alterar, remover ou atualizar os detalhes do seu estudo, entre em contato com register@clinicaltrials.gov. Assim que uma alteração for implementada em clinicaltrials.gov, ela também será atualizada automaticamente em nosso site .