Oncology Based On Online Review Semantic Analysis Study Of Patient Sentimental Portrait

In the past ten years,medical and health applications have continued to innovate and progress,and the penetration rate has gradually increased with the development and popularization of the Internet.In these community forums,patients discuss issues related to physical health,including information about their illnesses,symptoms,medications,and side effects,and some patients share their living conditions and emotional states during the illness to get emotional support.Cancer patients are a relatively active user group in the health forum.The forum has a large amount of text data containing emotional information.If you can use the large amount of text data in the online health community and obtain more detailed and true emotional information through text mining,then provide more detailed and accurate data on patient emotion monitoring.The article uses Python and tools such as octopus to crawl the emotional review texts about the emotions of patients with tumors stored in online health communities such as tumor-related topics and the platform for dancing with cancer,and emotional reviews of patients.After performing text preprocessing,sentiment analysis and other steps on the text,some portrait knowledge representation elements are extracted from the final text sentiment analysis annotation results,while the remaining part of the portrait knowledge representation elements need to be manually obtained from the relevant information of the patient's original review.All the acquired portrait knowledge representation elements are represented by ontology-based portrait knowledge representation methods for portrait knowledge representation.The patient's recessive emotion information is extracted from the constructed tumor disease patient ontology library to visually show the emotional state of the tumor patient.The research content includes:This article introduces the research theme of this article through the introduction of research background and significance and the review of domestic and foreign literature,that is,to construct emotional portraits for patients with tumor diseases.This paper proposes a model for constructing emotional portraits of patients with tumor diseases.For emotional portraits of online reviews of tumor patients,it is divided into two steps: acquisition and processing of portrait knowledge and representation of portrait knowledge.Among them,the core theory of portrait knowledge acquisition and processing is frame semantic analysis of online reviews.This method is mainly frame semantic theory;the core of portrait knowledge representation is ontologybased portrait knowledge representation method.The framework of online reviews is a semantic analysis.Through the preprocessing of a large number of text reviews on the online health community platform of cancer patients,a comprehensive medical sentiment dictionary is constructed.The medical sentiment dictionary includes information such as frames,semantic roles,sentiment words,and sentiment values;the role recognition adopts the semantic role labeling method based on pattern matching rules to realize the automatic labeling of the frame semantic role of the patient review text.Portrait knowledge representation by constructing a structural model of the user's portrait,this structural model specifically includes patient entities,dominant emotions,recessive emotions,and related data.The acquired knowledge representation elements are filled into the structural model,and visualize the result of the portrait.The research results of this article provide references for the acquisition,sharing and semantic query of emotional knowledge in the medical field,and provide basic resources and key technologies for medical emotional knowledge organization and knowledge retrieval.