Medication Recommendation System Based on Natural Language Processing for Patient Emotion Analysis

Haotian Zheng; Kangming Xu; Huiming Zhou; Yufu Wang; Guangze Su

doi:10.54097/v160aa61

Authors

Haotian Zheng
Kangming Xu
Huiming Zhou
Yufu Wang
Guangze Su

DOI:

https://doi.org/10.54097/v160aa61

Keywords:

Natural language processing (NLP); Artificial intelligence; Emotion analysis; Personalized recommendation; Comment analysis.

Abstract

Natural Language Processing (NLP) is an interdisciplinary field of computer science, artificial intelligence, and linguistics that focuses on the ability of computers to understand, process, generate, and simulate human language in order to achieve the ability to have natural conversations with humans. The underlying principles of natural language processing are at multiple levels, including linguistics, computer science, and statistics. It involves the study of language structure, semantics, grammar and pragmatics, as well as the statistical analysis and modeling of large-scale corpora. In the process of concrete implementation, it is necessary to process natural language at multiple levels. Based on this, this paper combined deep learning and natural language processing technology to conduct sentiment analysis on patients' comments, so as to recommend drugs that are more suitable for patients, thus achieving accurate drug prescribing and personalized recommendation.

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