{"title":"采矿合并症:简要调查","authors":"Giovanna Maria Dimitri","doi":"arxiv-2406.10696","DOIUrl":null,"url":null,"abstract":"In this manuscript we will present a brief overview of the comorbidity\nconcept. We will start by laying its foundations and its definitions and then\ndescribing the role that machine learning can hold in mining and defining it.\nThe purpose of this short survey is to present a brief overview of the\ndefinition of comorbidity as a concept, and showing some of the latest\napplications and potentialities for the application of natural language\nprocessing and text mining techniques.","PeriodicalId":501219,"journal":{"name":"arXiv - QuanBio - Other Quantitative Biology","volume":"36 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Mining comorbidities: a brief survey\",\"authors\":\"Giovanna Maria Dimitri\",\"doi\":\"arxiv-2406.10696\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this manuscript we will present a brief overview of the comorbidity\\nconcept. We will start by laying its foundations and its definitions and then\\ndescribing the role that machine learning can hold in mining and defining it.\\nThe purpose of this short survey is to present a brief overview of the\\ndefinition of comorbidity as a concept, and showing some of the latest\\napplications and potentialities for the application of natural language\\nprocessing and text mining techniques.\",\"PeriodicalId\":501219,\"journal\":{\"name\":\"arXiv - QuanBio - Other Quantitative Biology\",\"volume\":\"36 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-06-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - QuanBio - Other Quantitative Biology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2406.10696\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuanBio - Other Quantitative Biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2406.10696","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this manuscript we will present a brief overview of the comorbidity
concept. We will start by laying its foundations and its definitions and then
describing the role that machine learning can hold in mining and defining it.
The purpose of this short survey is to present a brief overview of the
definition of comorbidity as a concept, and showing some of the latest
applications and potentialities for the application of natural language
processing and text mining techniques.