Exploration and Practice of Constructing Structured Specialized Disease Database based on NLP for Medical Records

Corresponding author: ZHANG YANAN, 18964647796@163.com

DOI: 10.12201/bmr.202406.00007

•  

  Abstract: Objective/Meaning To slove the problems of coarse granularity and poor interoperability of unstructured electronic medical record generated during the diagnosis and treatment of psoriasis, this article provides a construction approach based on artificial intelligence technology to generate structured electronic medical records. A psoriasis specific disease database system is constructed to achieve the goal of precise and use medical record data. Process/Methods Transform unstructured electronic medical records into structured electronic medical records using artificial intelligence technologies such as templated input and natural language processing. Results/Conclusion The innovative practice of psoriasis specific disease database based on NLP has explored feasible solutions for constructing a standardized and standardized specific disease database. The multi center research and disease platform built on a single disease database has further achieved the scale development of disease databases, providing clinical researchers with unified, complete, and efficient data sources, improving the efficiency of clinical research work, and promoting high-quality development of clinical research work.

  Key words: NLP; templated input; natural language processing; structured electronic medical records; specific disease database

  Submit time: 7 June 2024

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

• 图表

• long si zhe, zhang wu jun. Data Governance-based Practice for Constructing Specialized Disease Database. 2022. doi: 10.12201/bmr.202207.00012

  Lianwanmin. Construction practice of cerebrovascular disease database based on Data Governance. 2022. doi: 10.12201/bmr.202210.00011

  wangyaoguo, tangshishi, liuhongze, anyuting, zhouyi. Research on optimization of osteoporosis disease database construction process based on local large model. 2024. doi: 10.12201/bmr.202410.00002

  niuyuxiang, geshanshan, wanglihua. Exploration and research of electronic medical record generation technology from traditional NLP to large language model. 2024. doi: 10.12201/bmr.202412.00080

  LIU Mi-mi, DU Guo-xia, ZHOU Yi, WU Bin, WU Xiao-ying. Construction and preliminary application of liver cirrhosis special disease database. 2021. doi: 10.12201/bmr.202104.00014

  Construction of specific medical records assessment system for CAP patients disease severity based on PDCA. 2024. doi: 10.12201/bmr.202409.00064

  Che Hebin, He Kunlun, Wu huan, Chen yuanyuan, Wang Wanling, Wang Fei, Liu Liyong. Research on the Preprocessing Method of Clinical Structured Data for Scientific Research. 2024. doi: 10.12201/bmr.202411.00076

  Che HeBin, Xu Hongli. Clinical Data Processing Process Specification in Medical Big Data Application Practice. 2021. doi: 10.12201/bmr.202109.00002

  zhangbaiping. Constructing patient diagnosis and treatment knowledge graph from relational database of EMR systemZHANG. 2021. doi: 10.12201/bmr.202110.00031

  Deng Jiale, Hu Zhensheng, Lian Wanmin, Hua Yunpeng, Zhou Yi. Research on entity recognition of liver cancer electronic medical records based on RoBERTa-CRF. 2023. doi: 10.12201/bmr.202303.00027

• ID	Submit time	Number	Download
  1	2024-03-24	bmr.202406.00007V1	Download

• Public  Anonymous  To author only Submit Comments