Cargando…
Development and Validation of an Automatic System for Intracerebral Hemorrhage Medical Text Recognition and Treatment Plan Output
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 tr...
Autores principales: | , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9028758/ https://www.ncbi.nlm.nih.gov/pubmed/35462698 http://dx.doi.org/10.3389/fnagi.2022.798132 |
_version_ | 1784691703896080384 |
---|---|
author | Deng, Bo Zhu, Wenwen Sun, Xiaochuan Xie, Yanfeng Dan, Wei Zhan, Yan Xia, Yulong Liang, Xinyi Li, Jie Shi, Quanhong Jiang, Li |
author_facet | Deng, Bo Zhu, Wenwen Sun, Xiaochuan Xie, Yanfeng Dan, Wei Zhan, Yan Xia, Yulong Liang, Xinyi Li, Jie Shi, Quanhong Jiang, Li |
author_sort | Deng, Bo |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9028758 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-90287582022-04-23 Development and Validation of an Automatic System for Intracerebral Hemorrhage Medical Text Recognition and Treatment Plan Output Deng, Bo Zhu, Wenwen Sun, Xiaochuan Xie, Yanfeng Dan, Wei Zhan, Yan Xia, Yulong Liang, Xinyi Li, Jie Shi, Quanhong Jiang, Li Front Aging Neurosci Neuroscience 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. Frontiers Media S.A. 2022-04-08 /pmc/articles/PMC9028758/ /pubmed/35462698 http://dx.doi.org/10.3389/fnagi.2022.798132 Text en Copyright © 2022 Deng, Zhu, Sun, Xie, Dan, Zhan, Xia, Liang, Li, Shi and Jiang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Deng, Bo Zhu, Wenwen Sun, Xiaochuan Xie, Yanfeng Dan, Wei Zhan, Yan Xia, Yulong Liang, Xinyi Li, Jie Shi, Quanhong Jiang, Li Development and Validation of an Automatic System for Intracerebral Hemorrhage Medical Text Recognition and Treatment Plan Output |
title | Development and Validation of an Automatic System for Intracerebral Hemorrhage Medical Text Recognition and Treatment Plan Output |
title_full | Development and Validation of an Automatic System for Intracerebral Hemorrhage Medical Text Recognition and Treatment Plan Output |
title_fullStr | Development and Validation of an Automatic System for Intracerebral Hemorrhage Medical Text Recognition and Treatment Plan Output |
title_full_unstemmed | Development and Validation of an Automatic System for Intracerebral Hemorrhage Medical Text Recognition and Treatment Plan Output |
title_short | Development and Validation of an Automatic System for Intracerebral Hemorrhage Medical Text Recognition and Treatment Plan Output |
title_sort | development and validation of an automatic system for intracerebral hemorrhage medical text recognition and treatment plan output |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9028758/ https://www.ncbi.nlm.nih.gov/pubmed/35462698 http://dx.doi.org/10.3389/fnagi.2022.798132 |
work_keys_str_mv | AT dengbo developmentandvalidationofanautomaticsystemforintracerebralhemorrhagemedicaltextrecognitionandtreatmentplanoutput AT zhuwenwen developmentandvalidationofanautomaticsystemforintracerebralhemorrhagemedicaltextrecognitionandtreatmentplanoutput AT sunxiaochuan developmentandvalidationofanautomaticsystemforintracerebralhemorrhagemedicaltextrecognitionandtreatmentplanoutput AT xieyanfeng developmentandvalidationofanautomaticsystemforintracerebralhemorrhagemedicaltextrecognitionandtreatmentplanoutput AT danwei developmentandvalidationofanautomaticsystemforintracerebralhemorrhagemedicaltextrecognitionandtreatmentplanoutput AT zhanyan developmentandvalidationofanautomaticsystemforintracerebralhemorrhagemedicaltextrecognitionandtreatmentplanoutput AT xiayulong developmentandvalidationofanautomaticsystemforintracerebralhemorrhagemedicaltextrecognitionandtreatmentplanoutput AT liangxinyi developmentandvalidationofanautomaticsystemforintracerebralhemorrhagemedicaltextrecognitionandtreatmentplanoutput AT lijie developmentandvalidationofanautomaticsystemforintracerebralhemorrhagemedicaltextrecognitionandtreatmentplanoutput AT shiquanhong developmentandvalidationofanautomaticsystemforintracerebralhemorrhagemedicaltextrecognitionandtreatmentplanoutput AT jiangli developmentandvalidationofanautomaticsystemforintracerebralhemorrhagemedicaltextrecognitionandtreatmentplanoutput |