Clinical Data Processing Process Specification in Medical Big Data Application Practice

Corresponding author: Xu Hongli, 648745357@qq.com

DOI: 10.12201/bmr.202109.00002

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  Abstract: Objective: To gradually standardize the clinical data processing process through real-world medical big data application practice in hospitals. Methods: The study of medical big data application practice in different scenarios is integrated, and different types of clinical data processing methods and considerations are sorted out. Results: At present, unstructured data and semi-structured data are converted into structured data items through string matching technology and natural language processing technology with manual collation, and structured data are processed in batch by program scripts to form clinical data processing process specification. Conclusion: Integrating medical big data from different business scenarios, we propose a clinical data processing process specification to promote the re-analysis and utilization of real-world big data in the medical field.

  Key words: Medical Big Data Application Practice；Clinical Data Processing； Process Specification; ; 

  Submit time: 15 September 2021

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
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