Development and Validation of an Automatic System for Intracerebral Hemorrhage Medical Text Recognition and Treatment Plan Output

作者全名："Deng, Bo; Zhu, Wenwen; Sun, Xiaochuan; Xie, Yanfeng; Dan, Wei; Zhan, Yan; Xia, Yulong; Liang, Xinyi; Li, Jie; Shi, Quanhong; Jiang, Li"

作者地址："[Deng, Bo; Sun, Xiaochuan; Xie, Yanfeng; Dan, Wei; Zhan, Yan; Xia, Yulong; Liang, Xinyi; Shi, Quanhong; Jiang, Li] Chongqing Med Univ, Dept Neurosurg, Affiliated Hosp 1, Chongqing, Peoples R China; [Zhu, Wenwen; Li, Jie] Chongqing Univ Sci & Technol, Sch Intelligent Technol & Engn, Chongqing, Peoples R China"

通信作者："Shi, QH; Jiang, L (通讯作者)，Chongqing Med Univ, Dept Neurosurg, Affiliated Hosp 1, Chongqing, Peoples R China.; Li, J (通讯作者)，Chongqing Univ Sci & Technol, Sch Intelligent Technol & Engn, Chongqing, Peoples R China."

来源：FRONTIERS IN AGING NEUROSCIENCE

ESI学科分类：NEUROSCIENCE & BEHAVIOR

WOS号：WOS:000792000900001

JCR分区：Q2

影响因子：4.8

年份：2022

卷号：14

期号：　

开始页：　

结束页：　

文献类型：Article

关键词：stroke; intracerebral hemorrhage (ICH); natural language processing (NLP); artificial intelligence (AI); neurosurgery emergency electrical medical record database (N-eEMRD)

摘要："The main purpose of the study was to explore a reliable way to automatically handle emergency cases, such as intracerebral hemorrhage (ICH). Therefore, an artificial intelligence (AI) system, named, H-system, was designed to automatically recognize medical text data of ICH patients and output the treatment plan. Furthermore, the efficiency and reliability of the H-system were tested and analyzed. The H-system, which is mainly based on a pretrained language model Bidirectional Encoder Representations from Transformers (BERT) and an expert module for logical judgment of extracted entities, was designed and founded by the neurosurgeon and AI experts together. All emergency medical text data were from the neurosurgery emergency electronic medical record database (N-eEMRD) of the First Affiliated Hospital of Chongqing Medical University, Chongqing Emergency Medical Center, and Chongqing First People's Hospital, and the treatment plans of these ICH cases were divided into two types. A total of 1,000 simulated ICH cases were randomly selected as training and validation sets. After training and validating on simulated cases, real cases from three medical centers were provided to test the efficiency of the H-system. Doctors with 1 and 5 years of working experience in neurosurgery (Doctor-1Y and Doctor-5Y) were included to compare with H-system. Furthermore, the data of the H-system, for instance, sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), and the area under the receiver operating characteristics curve (AUC), were calculated and compared with Doctor-1Y and Doctor-5Y. In the testing set, the time H-system spent on ICH cases was significantly shorter than that of doctors with Doctor-1Y and Doctor-5Y. In the testing set, the accuracy of the H-system's treatment plan was 88.55 (88.16-88.94)%, the specificity was 85.71 (84.99-86.43)%, and the sensitivity was 91.83 (91.01-92.65)%. The AUC value of the H-system in the testing set was 0.887 (0.884-0.891). Furthermore, the time H-system spent on ICH cases was significantly shorter than that of doctors with Doctor-1Y and Doctor-5Y. The accuracy and AUC of the H-system were significantly higher than that of Doctor-1Y. In addition, the accuracy of the H-system was more closed to that of Doctor-5Y. The H-system designed in the study can automatically recognize and analyze medical text data of patients with ICH and rapidly output accurate treatment plans with high efficiency. It may provide a reliable and novel way to automatically and rapidly handle emergency cases, such as ICH."

基金机构：National Natural Science Foundation for Youth of China [81701226]; Chongqing Medical Scientific Research Project (Joint project of Chongqing Health Commission and Science and Technology Bureau) [2022MSXM041]; Science and Technology Innovation Project of Chongqing University of Science and Technology [YKJCX2020834]

基金资助正文："This study was funded by the National Natural Science Foundation for Youth of China (no. 81701226), Chongqing Medical Scientific Research Project (Joint project of Chongqing Health Commission and Science and Technology Bureau) (no. 2022MSXM041), and Science and Technology Innovation Project of Chongqing University of Science and Technology (no. YKJCX2020834)."