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Published on: August 15, 2025
A Text Structuring Method for Chinese Medical Text Based on Temporal Information
Runtong Zhang1, Fuzhi Chu2, Donghua Chen3
1Department of Information Management, Beijing Jiaotong University, Beijing 100044, China. rtzhang@bjtu.edu.cn.
This study introduces a new method to structure Chinese Electronic Medical Records (EMRs), transforming complex free text into chronological data. This approach simplifies EMRs for advanced medical research and analysis.
Area of Science:
- Medical Informatics
- Natural Language Processing
- Data Science
Background:
- Chinese Electronic Medical Records (EMRs) contain valuable unstructured text data.
- Processing this complex medical free text is challenging for computational analysis.
- EMRs include crucial information like temporal data, symptoms, and lab results.
Purpose of the Study:
- To develop a novel text structuring method for Chinese EMRs.
- To extract and reorganize knowledge from EMR free text chronologically.
- To enhance the usability of EMR data for medical research.
Main Methods:
- Proposed a novel text structuring technique.
- Extracted knowledge from EMR free text.
- Reorganized extracted information based on temporal data.
- Implemented entropy-based algorithms for performance comparison.
Main Results:
- The proposed method significantly reduces the complexity of EMR text.
- Successfully structured unstructured EMR free text into a chronological format.
- Demonstrated superior performance compared to entropy-based algorithms.
Conclusions:
- The novel text structuring method effectively processes complex Chinese EMRs.
- Structured EMR data facilitates further medical analysis and research.
- This work provides a valuable tool for leveraging EMR knowledge bases.
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