{"title":"ChatGPT's ability to classify virtual reality studies in cardiology.","authors":"Yuichiro Nakaya, Akinori Higaki, Osamu Yamaguchi","doi":"10.1093/ehjdh/ztad026","DOIUrl":null,"url":null,"abstract":"We recently published a novel categorization of studies related to virtual reality (VR) in your journal, European Heart Journal—Digital Health . 1 Our categorization is based on the usage of VR devices, where type A studies refer to those in which healthcare providers use VR devices and type B studies refer to those in which patients use them. Using this sim-ple definition, we clarified the study trends and characteristics of the two research directions. In this study, we used a classical natural language processing (NLP) methodology, specifically ‘term frequency– inverse document frequency’ to develop an automatic abstract categorizer, which is available as a web application at https://ahigaki-vr-categorizer-str-app-gb1m6v.streamlit.app","PeriodicalId":72965,"journal":{"name":"European heart journal. Digital health","volume":"4 3","pages":"141-142"},"PeriodicalIF":3.9000,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/3f/a5/ztad026.PMC10232268.pdf","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"European heart journal. Digital health","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/ehjdh/ztad026","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
引用次数: 2
Abstract
We recently published a novel categorization of studies related to virtual reality (VR) in your journal, European Heart Journal—Digital Health . 1 Our categorization is based on the usage of VR devices, where type A studies refer to those in which healthcare providers use VR devices and type B studies refer to those in which patients use them. Using this sim-ple definition, we clarified the study trends and characteristics of the two research directions. In this study, we used a classical natural language processing (NLP) methodology, specifically ‘term frequency– inverse document frequency’ to develop an automatic abstract categorizer, which is available as a web application at https://ahigaki-vr-categorizer-str-app-gb1m6v.streamlit.app