基于数据融合的实验室数据质检追溯分析系统及方法
By screening abnormal parameters, calculating the trust index, and constructing a network graph, the problem of being unable to quickly identify laboratory data anomalies in existing technologies has been solved. This enables accurate traceability of laboratory data and identification of deep-seated quality problems, thereby improving the efficiency and accuracy of laboratory data quality inspection.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- 江苏省软件产品检测中心
- Filing Date
- 2026-05-07
- Publication Date
- 2026-07-17
AI Technical Summary
Existing laboratory data quality inspection and traceability analysis methods cannot quickly pinpoint laboratory data that leads to abnormal experimental results, cannot identify deep-seated quality problems, and are insufficient to meet the high precision and strong compliance requirements of modern laboratories.
By screening abnormal laboratory environmental parameters and equipment operating status parameters, calculating the trust index, constructing a network diagram to analyze trust pain points and quality inspection traceability anomaly interception points, determining the quality inspection traceability path, and achieving accurate traceability of abnormal data.
Quickly pinpoint the scope of anomalies in laboratory data quality inspection and traceability, identify deeper quality issues, improve the efficiency and accuracy of quality inspection and traceability, and ensure the repeatability and compliance of experimental results.
Smart Images
Figure CN122174122B_ABST