Analysis of Artificial Intelligence and Natural Language Processing Significance as Expert Systems Support for E-Health Using Pre-Train Deep Learning Models

Mah, Pascal Muam

doi:10.56578/ataiml010201

Cited by 3 publications

(1 citation statement)

References 40 publications

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“…With the rapid development of information technology, the application of artificial intelligence in various fields is becoming increasingly widespread. As an important branch of artificial intelligence, natural language processing (NLP) has received extensive attention in several fields, such as linguistics, computer science, and information engineering [1][2][3][4][5]. In recent years, the research of NLP-based students' composition evaluation models has become a hot topic.…”

Section: Introductionmentioning

confidence: 99%

Students’ Composition Evaluation Model Based on Natural Language Processing Algorithm

Wang¹,

Deng²

2023

Int. J. Emerg. Technol. Learn.

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It is subjective, time consuming and labor intensive to evaluate students’ compositions. Use of natural language processing (NLP) technology effectively improves the evaluation efficiency and reduces the burden on teachers. In order to overcome the problems of traditional models, such as over-fitting and poor generalization ability, this research studied a students’ composition evaluation model based on an NLP algorithm. A students’ composition evaluation model based on a multi-task learning framework was proposed, which completed three sub-tasks simultaneously using the NLP algorithm. Three different encoding methods were used; namely, convolutional neural network (CNN), recurrent neural network (RNN), and long short-term memory (LSTM), which captured text information from multiple perspectives. A new pairing pre-training mode was built, which aimed to help build an NLP-based students’ composition evaluation model based on the multi-task learning framework, thus alleviating the deviation caused by excessive correlation. The experimental results verified that the constructed model and the proposed method were effective.

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Section: Introductionmentioning

confidence: 99%

Students’ Composition Evaluation Model Based on Natural Language Processing Algorithm

Wang¹,

Deng²

2023

Int. J. Emerg. Technol. Learn.

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Possibilities of using artificial intelligence and natural language processing to analyse legal norms and interpret them

Serediuk

2024

SLS

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The study aaddressed the possibilities of using information technology and natural language in the study of legal norms. The study aimed to develop methods for using artificial intelligence and natural language processing to analyse jurisprudence. To achieve this goal, automatic strategies were created to recognise the main topics in legal texts, identify key legal concepts and analyse the structure of documents. The results of the study included an analysis of existing methods of using technology and natural language to analyse legal norms. The methods used included machine and deep learning, syntactic and semantic analysis, an automated classification system, relative analytics, and decision prediction. In addition, new methods of analysing legal texts based on artificial intelligence and natural language processing were introduced. These methods included the use of a thematic model that automatically identifies the main themes in legal texts, as well as automatic detection of legal concepts, which identifies key concepts. In addition, neural networks were used to analyse the structure of legal documents, which allows for more accurate recognition and analysis of various structural elements in documents. Automatic text generation based on legal information and ways to classify legal texts was also introduced. Thus, the main results were the automation of the process of analysing and understanding legal texts, an increase in the efficiency and accuracy of identifying thematic patterns and key legal concepts, and improved accessibility and speed of legal information processing. The results obtained indicate a great potential for the use of technological tools in jurisprudence, which can significantly improve the quality and accessibility of legal services, contributing to more efficient resolution of legal issues

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Education Changes Child Health Behavior in China: A Mediating Role of Information Technology

Zhu

Jian-ying

2023

am j health behav

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Objectives: In this study, we aimed to explore the impact of education in changing child health behavior in China and mediating role of information technology. Methods: The theoretical framework of this study incorporated variables including mental health literacy, health education, information technology, and health behavior. This is a quantitative study that has utilized secondary data for determining the results. Based on the cross-sectional data collection method, 778 responses were considered for structural equation modeling. Smart PLS 3 was used to validate the research hypotheses. Results: We found that health education and mental health literacy have a substantial impact on Chinese child health behavior. Furthermore, our data also revealed that the mediating role of information technology is useful for children's health behavior enhancement. Conclusions: The health behavior of children is influenced by education and information technology mediates the health education-health behavior relationship.

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Analysis of Artificial Intelligence and Natural Language Processing Significance as Expert Systems Support for E-Health Using Pre-Train Deep Learning Models

Cited by 3 publications

References 40 publications

Students’ Composition Evaluation Model Based on Natural Language Processing Algorithm

Students’ Composition Evaluation Model Based on Natural Language Processing Algorithm

Possibilities of using artificial intelligence and natural language processing to analyse legal norms and interpret them

Education Changes Child Health Behavior in China: A Mediating Role of Information Technology

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