Multi-center Validation Study of a Large Language Model-based Intelligent Agent for Blood Cell Analysis
I. Study Background: Currently, in most medical institutions, the review of blood cell analysis still heavily relies on manual verification by laboratory staff. This process requires a comprehensive analysis of instrument parameters, alarm flags, historical comparison results, and, when necessary, microscopic examination. However, with the increasing volume of test samples and the high concentration of review tasks during peak hours, the traditional manual review model increasingly shows problems such as prolonged turnaround time (TAT), uneven workload distribution, and decreased consistency in reviews. In recent years, intelligent review systems based on Large Language Models (LLM) have shown potential in analyzing abnormal results and stratifying sample risks by integrating preset rules, clinical diagnostic information, and multi-dimensional laboratory data, which is expected to optimize the review workflow.
II. Study Objective: To evaluate the difference in overall sample review turnaround time between the experimental process and the control process during the formal study phase, and to test its superiority.
III. Subjects: The investigators need to recruit approximately 20,000 subjects, regardless of age or gender.
IV. Study Procedures: If participants agree to participate in the study, participants only need to allow us to use participants test results after participants have completed your routine blood test (CBC).
V. Risks and Benefits:
- Risks: This study poses no risk to the subjects. The investigators only use the result data of patients after participants have had their routine blood test; there is no need for patients to undergo additional blood draws.
- Benefits: It will shorten the turnaround time for routine blood test results and share the workload of doctors in reviewing these results.
VI. Privacy: All of participants information will be kept strictly confidential and will only be used for this scientific research.
調査の概要
研究の種類
入学 (推定)
参加基準
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
サンプリング方法
調査対象母集団
説明
Inclusion Criteria:
- Subjects who underwent routine blood tests in the outpatient, emergency, or inpatient departments of the participating centers during the study period.
Corresponding samples must have complete instrument results, review trails, and report timestamp records.
Approved for inclusion by the Ethics Committee.
Exclusion Criteria:
- Samples collected during periods of instrument malfunction or interface transmission anomalies.
Missing key research data, particularly samples where the final review conclusion or key timestamps cannot be confirmed.
Subjects or their legal representatives explicitly refuse to participate in the study.
研究計画
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 |
介入・治療 |
|---|---|
|
LLM-Assisted Review Group
|
This study introduces an intelligent auxiliary review system based on a medical Large Language Model (LLM), aimed at optimizing the traditional CBC report review process. The core functions and intervention mechanisms are as follows: Multi-source Data Integration: The system integrates seamlessly with the Laboratory Information System (LIS) to automatically retrieve patient demographics (age, sex), current CBC indices, historical results, and clinical diagnoses. Deep Analysis and Anomaly Detection: Unlike traditional rule-based auto-verification, this system leverages the reasoning capability of LLMs to perform multidimensional clinical logic checks. It identifies out-of-range values and interprets their clinical significance by combining them with patient history (e.g., distinguishing physiological fluctuations from pathological changes). |
|
Standard Manual Review Group
|
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 |
時間枠 |
|---|---|
|
Overall Report Turnaround Time
時間枠：one year
|
one year
|
協力者と研究者
研究記録日
主要日程の研究
研究開始 (推定)
一次修了 (推定)
研究の完了 (推定)
試験登録日
最初に提出
QC基準を満たした最初の提出物
最初の投稿 (実際)
学習記録の更新
投稿された最後の更新 (実際)
QC基準を満たした最後の更新が送信されました
最終確認日
詳しくは
本研究に関する用語
その他の研究ID番号
- KY2026-084
この情報は、Web サイト clinicaltrials.gov から変更なしで直接取得したものです。研究の詳細を変更、削除、または更新するリクエストがある場合は、register@clinicaltrials.gov。 までご連絡ください。 clinicaltrials.gov に変更が加えられるとすぐに、ウェブサイトでも自動的に更新されます。