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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
Structuring of free-text diagnostic report
Hirofumi Fujii1, Hiromasa Yamagishi, Yutaka Ando
1Functional Imaging Division, Research Center for Innovative Oncology, National Cancer Center Hospital East, Kashiwa, Japan. hifujii@east.ncc.go.jp
This study introduces a semantic analysis system to convert free-text diagnostic reports into structured data. The system effectively extracts description units, improving the secondary investigation of medical reports.
Area of Science:
- Medical Informatics
- Natural Language Processing
- Radiology
Background:
- Free-text diagnostic reports hinder secondary data analysis.
- Structured reports are crucial for efficient information retrieval and research.
Purpose of the Study:
- To develop and evaluate a system for automatically extracting description units from free-text diagnostic reports.
- To enhance the structure of diagnostic reports using semantic analysis.
Main Methods:
- Defined rules for creating description units.
- Developed a system for automatic extraction of these units.
- Applied the system to cerebral perfusion scintigram reports and compared results with physician interpretations.
Main Results:
- The system's recall rate improved with increased data, reaching saturation around 85% with 300 cases.
- Five dictionaries of description units were generated.
Conclusions:
- The proposed semantic analysis system is useful for evaluating reports of cerebral perfusion scintigrams.
- Automated structuring of diagnostic reports facilitates secondary investigations.
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