Text mining and analysis of treatise on febrile diseases based on natural language processing

Zhao, Kai; Shi, Na; Sa, Zhen; Wang, Hua-Xing; Lu, Chenyang; Xu, Xiaoying

doi:10.4103/wjtcm.wjtcm_28_19

Cited by 16 publications

(4 citation statements)

References 3 publications

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“…Additionally, these texts highlighted that foods offered not only vital nutrition but also therapeutic properties similar to drugs [4][5][6] . During the Eastern Han Dynasty, Zhang Zhongjing's Treatise on Cold Pathogenic and Miscellaneous Diseases (伤寒杂病论) and Synopsis of Formulas for the Golden Chamber (金匮要略方论) integrated the concepts of food and medicine [7,8] . In the Tang Dynasty, Sun Simiao's Essential Recipes for Emergent Use Worth A Thousand Gold (备急千金要方) emphasized dietary therapy, highlighting the medicinal value of foods [9] .…”

Section: Historical Insights Into Medicine and Food Homology (Mfh)mentioning

confidence: 99%

The Evolution and Significance of Medicine and Food Homology

Zhong,

Tang,

et al. 2024

Acupuncture and Herbal Medicine

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Section: Historical Insights Into Medicine and Food Homology (Mfh)mentioning

confidence: 99%

The Evolution and Significance of Medicine and Food Homology

Zhong,

Tang,

et al. 2024

Acupuncture and Herbal Medicine

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“…; and (2) training or construction of a classifier based on the selected features followed by classification of new inputted unstructured data by the trained classifier. Among the 19 studies using shallow ML methods, the classifiers included decision tree (DT) [30,43], naive Bayes (NB) [53], support vector machine (SVM) [27,40,51,53], hidden Markov model (HMM) [19,47], maximum entropy Markov model (MEMM) [19,47], conditional random fields (CRF) [19,30,[45][46][47][48][49][50]53], heterogeneous factor graph [20], other NLP tools [67], etc. e unique tree structure of DT enables it to deal with continuous sequence data in IE tasks, but it ignores the correlation between attributes and easily causes overfitting results.…”

Section: Machine Learning Models Shallow Machine Learningmentioning

confidence: 99%

Information Extraction from the Text Data on Traditional Chinese Medicine: A Review on Tasks, Challenges, and Methods from 2010 to 2021

Zhang

Huang

Wang

et al. 2022

Evidence-Based Complementary and Alternative Medicine

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Background. The practice of traditional Chinese medicine (TCM) began several thousand years ago, and the knowledge of practitioners is recorded in paper and electronic versions of case notes, manuscripts, and books in multiple languages. Developing a method of information extraction (IE) from these sources to generate a cohesive data set would be a great contribution to the medical field. The goal of this study was to perform a systematic review of the status of IE from TCM sources over the last 10 years. Methods. We conducted a search of four literature databases for articles published from 2010 to 2021 that focused on the use of natural language processing (NLP) methods to extract information from unstructured TCM text data. Two reviewers and one adjudicator contributed to article search, article selection, data extraction, and synthesis processes. Results. We retrieved 1234 records, 49 of which met our inclusion criteria. We used the articles to (i) assess the key tasks of IE in the TCM domain, (ii) summarize the challenges to extracting information from TCM text data, and (iii) identify effective frameworks, models, and key findings of TCM IE through classification. Conclusions. Our analysis showed that IE from TCM text data has improved over the past decade. However, the extraction of TCM text still faces some challenges involving the lack of gold standard corpora, nonstandardized expressions, and multiple types of relations. In the future, IE work should be promoted by extracting more existing entities and relations, constructing gold standard data sets, and exploring IE methods based on a small amount of labeled data. Furthermore, fine-grained and interpretable IE technologies are necessary for further exploration.

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“…(2) Well-known foreign YouTube uses Python to write some important services The traditional sensor network is applied to usually adopt the wired way to carry on the data transmission. Wired sensor networks generally consist of wired sensor nodes, control systems, and wired communication modules [13,14]. After the wired sensor node collects data with its built-in sensor equipment, it provides a data communication drive for the node through the control system and transmits the data to the data center through the communication module to complete the network of the node [15].…”

Section: Python Language and Intelligent Sensormentioning

confidence: 99%

Real-Time Analysis of Youth Emotion Based on Python Language and Smart Sensor Network

Yan

2022

Mobile Information Systems

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Adolescents’ emotional changes will have a huge impact on themselves; perhaps, they do not understand themselves. However, according to research, many behaviors of adolescents are often accompanied by emotional changes, and the occurrence of these changes will also bring about their unconsciousness. This article first introduces the research background, significance, and development status of smart home sensors and young people’s emotions at home and abroad. This article then gives a detailed introduction to the Python language, intelligent sensor networks, and real-time analysis of youth emotions. In the introduction, it mainly explains the design of the intelligent sensor network system and introduces the system architecture and software and hardware design of the wireless sensor network in detail. In the hardware part, it mainly gives a brief overview of information collection, data transmission, and data processing. In the software part, the embedded software design of three types of network nodes and the control center software design based on Python are given. Finally, the neural network algorithm is used to realize the real-time analysis of young people’s emotions, and the recognition rate of multiple algorithms and the data situation of multiple emotional factors are tested at the same time. The results show that the highest recognition rate of 58.4% can be achieved on the validation set of the HAPPEI database after preprocessing, which is higher than the recognition result obtained by directly training the network using the training set of the HAPPEI database.

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Text mining and analysis of treatise on febrile diseases based on natural language processing

Cited by 16 publications

References 3 publications

The Evolution and Significance of Medicine and Food Homology

The Evolution and Significance of Medicine and Food Homology

Information Extraction from the Text Data on Traditional Chinese Medicine: A Review on Tasks, Challenges, and Methods from 2010 to 2021

Real-Time Analysis of Youth Emotion Based on Python Language and Smart Sensor Network

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