Artificial Intelligence for Screening Chinese Electronic Medical Record and Biobank Information.

Journal: Biopreservation and biobanking
PMID:

Abstract

To establish a structured and integrated platform of clinical data and biobank data, and a client to retrieve these data. Initially, the hospital information system (HIS) and biobank information system (BIS) were integrated through the patients' ID numbers. Then, natural language processing (NLP) was used to process the integrated unstructured clinical information. A query interface was designed for this system, which enabled researchers to retrieve clinical or biobank data. Finally, several queries were listed and manually checked to test the retrieval performance of the system. The construction of the biobank screening system (BSS) was completed, and the data were structured. The BSS took an average of 2 seconds to perform a search for target patients/samples. The retrieval results were consistent with the HIS and BIS. For complex queries, we manually checked the retrieved patients/samples, and the system's accuracy was 100%. This NLP-based system improved biological sample screening and using of clinical data. We will continue to improve this system, enhance resource sharing, and promote the development of translational medicine.

Authors

  • Xiaoqing Li
  • Jiang Han
    Department of Biobank, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Shaodian Zhang
    Biomedical Informatics, Columbia University, New York, NY, USA.
  • Ken Chen
    The Genome Institute, Washington University in St. Louis, St. Louis, Missouri, United States of America.
  • Liebin Zhao
    School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Yi He
    National Institutes for Food and Drug Control, 2 Tiantan Xili, Beijing 100050, China.
  • Shijian Liu
    Shanghai Children's Medical Center, Shanghai, China.