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

2026年7月18日 更新者：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.

調査の概要

状態

募集

条件

詳細な説明

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.

研究の種類

観察的

入学 (推定)

2000

連絡先と場所

このセクションには、調査を実施する担当者の連絡先の詳細と、この調査が実施されている場所に関する情報が記載されています。

研究連絡先

研究場所

  • 中国
    • Guangdong
      • Guangzhou、Guangdong、中国、510000
        • 募集
        • Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University
        • コンタクト：
      • Shantou、Guangdong、中国、516600
        • 募集
        • Shenshan Medical Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University
        • コンタクト：
    • Jiangxi
      • Ganzhou、Jiangxi、中国、341000
        • 募集
        • Ganzhou People's Hospital
        • コンタクト：

参加基準

研究者は、適格基準と呼ばれる特定の説明に適合する人を探します。これらの基準のいくつかの例は、人の一般的な健康状態または以前の治療です。

適格基準

就学可能な年齢

  • 子
  • 大人
  • 高齢者

健康ボランティアの受け入れ

いいえ

サンプリング方法

非確率サンプル

調査対象母集団

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.

説明

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.

研究計画

このセクションでは、研究がどのように設計され、研究が何を測定しているかなど、研究計画の詳細を提供します。

研究はどのように設計されていますか？

デザインの詳細

コホートと介入

グループ/コホート
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.

この研究は何を測定していますか？

主要な結果の測定

結果測定
メジャーの説明
時間枠
Diagnostic Accuracy of UroAgent
時間枠：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.

二次結果の測定

結果測定
メジャーの説明
時間枠
Expert Subjective Accuracy Rating
時間枠：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
時間枠：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
時間枠：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
時間枠：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.

協力者と研究者

ここでは、この調査に関係する人々や組織を見つけることができます。

スポンサー

Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

協力者

Shenshan Medical Center, Memorial Hospital of Sun Yat-sen University
Ganzhou City People's Hospital

研究記録日

これらの日付は、ClinicalTrials.gov への研究記録と要約結果の提出の進捗状況を追跡します。研究記録と報告された結果は、国立医学図書館 (NLM) によって審査され、公開 Web サイトに掲載される前に、特定の品質管理基準を満たしていることが確認されます。

主要日程の研究

研究開始 (実際)

2025年4月1日

一次修了 (推定)

2026年12月31日

研究の完了 (推定)

2027年6月30日

試験登録日

最初に提出

2026年7月12日

QC基準を満たした最初の提出物

2026年7月18日

最初の投稿 (実際)

2026年7月23日

学習記録の更新

投稿された最後の更新 (実際)

2026年7月23日

QC基準を満たした最後の更新が送信されました

2026年7月18日

最終確認日

2026年7月1日

詳しくは

本研究に関する用語

キーワード

追加の関連 MeSH 用語

その他の研究ID番号

  • SYSKY-2025-151-03

個々の参加者データ (IPD) の計画

個々の参加者データ (IPD) を共有する予定はありますか?

いいえ

IPD プランの説明

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.

医薬品およびデバイス情報、研究文書

米国FDA規制医薬品の研究

いいえ

米国FDA規制機器製品の研究

いいえ

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