Word Embedding Bootstrapped Deep Active Learning Method to Information Extraction on Chinese Electronic Medical Record

Ma, Qunsheng; Cen, Xingxing; Yuan, Junyi; Hou, Xiaolin

doi:10.1007/s12204-021-2285-5

Cited by 6 publications

(3 citation statements)

References 13 publications

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“…[5][6][7][8] Traditional Chinese Exercise (TCE), rooted in the ancient traditions of Chinese medicine, encompasses a combination of physical exercises, breathing techniques, and mental focus. [9] TCE have been extensively applied as a therapeutic modality, dating back to the Qin and Han dynasties, and have been historically associated with the management of respiratory ailments. [10][11][12] Furthermore, previous studies have demonstrated that TCE modulates the immune system and enhances respiratory muscle strength, resulting in reduced dyspnea, improved exercise tolerance, and enhanced quality of life among patients with COPD.…”

Section: This Study Was Supported By the Shanghai Municipal Health Co...mentioning

confidence: 99%

Traditional Chinese exercise in chronic obstructive pulmonary disease: An overview of systematic reviews

Han,

Wang,

Zhu

et al. 2024

Medicine

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This study aims to critically reassess existing systematic reviews (SR) on Traditional Chinese Exercises (TCE) for treating Chronic Obstructive Pulmonary Disease (COPD). The primary objectives include synthesizing available evidence, evaluating the methodological quality of reviews and overall evidence, and providing comprehensive insights into the effectiveness of different TCE types in managing COPD. Sinomed, CNKI, VIP, Wanfang, PubMed, Cochrane Library, and Web of Science were searched from inception to April 2023 for SR literature on the treatment of COPD with TCE. The extracted data from the included SRs encompassed various aspects such as general information, study population, intervention measures, meta-analysis results, and conclusions. The methodological quality of the included SRs was assessed using the AMSTAR II tool. Additionally, the GRADE tool was used to determine the evidence level of outcome indicators. This study included 17 SRs and 4 types of TCE. The CCA was 0.041, indicating a slight overlap between the primary studies. Notably, one study was rated as low quality on the AMSTAR II scale, while the rest were classified as critically low quality. The results from the GRADE evaluation revealed 26 pieces of very low-quality evidence, 55 pieces of low-quality evidence, and 17 pieces of moderate-quality evidence. The moderate-quality evidence suggests that Liuzijue effectively improves TCM syndrome scores in patients with COPD. Additionally, low-quality evidence suggests that Liuzijue improves patients’ lung function (FEV1, FVC) and quality of life (CAT, MRC/mMRC). Similarly, low-quality evidence suggests that Baduanjin can improve patients’ lung function (FEV1%, FVC) and quality of life (SGRQ). Low-quality evidence also suggests that Health Qigong can significantly improve patients’ exercise endurance (6MWD). No SR reported TCE-related adverse reactions. TCE interventions are effective and safe in the treatment of COPD. Different types of TCE have varying effects on outcomes in COPD patients. However, these findings are limited by the generally low methodological and evidence quality of the included SRs. Therefore, it is strongly recommended to improve study designs to obtain higher-quality clinical evidence and to strictly follow SR protocols.

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Section: This Study Was Supported By the Shanghai Municipal Health Co...mentioning

confidence: 99%

Traditional Chinese exercise in chronic obstructive pulmonary disease: An overview of systematic reviews

Han,

Wang,

Zhu

et al. 2024

Medicine

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“…Vectorization of text is needed before sentiment analysis using deep learning models. Word embedding, also known as a word vector, is a distributed feature representation of a word generated by training a neural network language model [24] . There are currently six publicly known and well-known models for generating word vectors: HLBL, SENNA, Huang's, Turian's, Glove, and Word2vec.…”

Section: Literature Reviewmentioning

confidence: 99%

Online Reviews Sentiment Analysis and Product Feature Improvement with Deep Learning

Cao

Yin

et al. 2023

ACM Trans. Asian Low-Resour. Lang. Inf. Process.

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The text mining of online reviews is currently a popular research direction of e-commerce and is considered the next blue ocean. Online reviews can dig out consumer preferences and provide theoretical guidance for the improvement of product features. However, current research mostly focuses on sentiment analysis methods and rarely involves feature extraction and large-scale data recognition. This paper uses word segmentation technology to create a new feature extraction method. With long-short term memory(LSTM) neural network and latent dirichlet allocation(LDA) topic model, we proposes a product feature improvement model (Consumer online reviews-Extract short text-Sentiment analysis-Cluster feature, CESC). The model can derive the product features and attitudes that consumers prefer based on consumer online reviews, and use it to improve product features. According to the experimental results of three electronic products sold on the e-commerce platform, the model can effectively dig out consumer preferences for online reviews. Enterprises can improve the quality of products and services, better meet the needs of consumers, promote consumers’ consumption, and achieve the enterprises’ goals and values.

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“…Xanthidis and Xanthidou [9] designed an error-correcting code hash function and constructed an anonymization algorithm for privacy protection, which effectively controls the access rights of other users, while ensuring the safe sharing of data between patients and doctors. Ma et al [10] proposed an authentication mechanism and authorized access mechanism for the users who make access requests and effectively solved the patients' control of EMR data and the authorized access to EMR data.…”

Section: Introductionmentioning

confidence: 99%

Information Sharing and Privacy Protection of Electronic Nursing Record Management System

2022

Scientific Programming

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The traditional centralized storage of traditional electronic medical records (EMRs) faces problems like data leakage, data loss, and EMR misplacement. The current protection measures for patients’ privacy in EMRs cannot withstand the fast-developing password cracking technologies and frequency cyberattacks. This paper intends to innovate the information sharing and privacy protection of electronic nursing records (ENRs) management system. Specifically, the signature interception technology was introduced to EMRs, the different phases of certificateless signature interception scheme were depicted, and the validation procedures of the scheme were designed. Then, the six phases of ENR information sharing protocol based on alliance blockchain were described in detail. Finally, an end-to-end memory neural network was constructed for ENR classification. The proposed management scheme was proved effective through experiments.

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Word Embedding Bootstrapped Deep Active Learning Method to Information Extraction on Chinese Electronic Medical Record

Cited by 6 publications

References 13 publications

Traditional Chinese exercise in chronic obstructive pulmonary disease: An overview of systematic reviews

Traditional Chinese exercise in chronic obstructive pulmonary disease: An overview of systematic reviews

Online Reviews Sentiment Analysis and Product Feature Improvement with Deep Learning

Information Sharing and Privacy Protection of Electronic Nursing Record Management System

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