Multi-source data fusion management method and system for medical record information

By conducting semantic mapping and timing feature analysis of multi-source data in medical institutions, a unified medical record data view is generated, the problem of semantic correlation neglect in medical record management is solved, efficient integration and deep understanding of multi-source data is achieved, and the quality of medical services and decision-making support capabilities are improved.

CN120452824AActive Publication Date: 2025-08-08AFFILIATED HUSN HOSPITAL OF FUDAN UNIV
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Patent Information

Application Number
CN202510612121.X
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-05-13
Publication Date
2025-08-08
Estimated Expiration
2045-05-13

AI Technical Summary

Technical Problem

Existing medical record management methods ignore the semantic correlation between data, limiting the ability to deeply understand and explore medical record information, especially in the diagnosis and treatment of complex diseases, it is difficult to provide comprehensive information support.

Method used

By collecting data from the electronic medical record system, medical imaging workstation and inspection information system of medical institutions, semantic mapping and conceptual association are performed based on the medical ontology knowledge graph, dynamic timing feature analysis is performed using the timing feature extractor, and finally heterogeneous data fusion is performed to generate a unified medical record data view.

Benefits of technology

It has achieved effective integration and display of medical record data from different sources under the same framework, improved the quality and efficiency of medical services, supported precise medical treatment and personalized treatment, and improved the performance of decision support systems.

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Abstract

The invention relates to a multi-source data fusion management method and system for medical record information, and the method comprises the following steps: carrying out the data collection of an electronic medical record system, a medical image workstation and an inspection information system of a medical institution, and obtaining an original medical record data set; performing semantic mapping and concept association on the original medical record data set based on a preset medical ontology knowledge graph to obtain a semantic association medical record information network; performing dynamic time sequence feature analysis on the semantic association medical record information network through a time sequence feature extractor to obtain a time sequence medical record feature sequence; and carrying out heterogeneous data fusion on the time sequence medical record feature sequence to obtain a unified medical record data view, so that the technical problem that the capability of deeply understanding and mining medical record information is limited due to the fact that an existing medical record management method usually ignores semantic relevance between data is solved.
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