{"title":"Getting to Know Named Entity Recognition: Better Information Retrieval.","authors":"Borui Zhang","doi":"10.1080/02763869.2024.2335139","DOIUrl":null,"url":null,"abstract":"<p><p>Named entity recognition (NER) is a powerful computer system that utilizes various computing strategies to extract information from raw text input, since the early 1990s. With rapid advancement in AI and computing, NER models have gained significant attention and been serving as foundational tools across numerus professional domains to organize unstructured data for research and practical applications. This is particularly evident in the medical and healthcare fields, where NER models are essential in efficiently extract critical information from complex documents that are challenging for manual review. Despite its successes, NER present limitations in fully comprehending natural language nuances. However, the development of more advanced and user-friendly models promises to improve work experiences of professional users significantly.</p>","PeriodicalId":39720,"journal":{"name":"Medical Reference Services Quarterly","volume":"43 2","pages":"196-202"},"PeriodicalIF":0.0000,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Medical Reference Services Quarterly","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/02763869.2024.2335139","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/5/9 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 0
Abstract
Named entity recognition (NER) is a powerful computer system that utilizes various computing strategies to extract information from raw text input, since the early 1990s. With rapid advancement in AI and computing, NER models have gained significant attention and been serving as foundational tools across numerus professional domains to organize unstructured data for research and practical applications. This is particularly evident in the medical and healthcare fields, where NER models are essential in efficiently extract critical information from complex documents that are challenging for manual review. Despite its successes, NER present limitations in fully comprehending natural language nuances. However, the development of more advanced and user-friendly models promises to improve work experiences of professional users significantly.
期刊介绍：
This highly acclaimed, peer-reviewed journal is an essential working tool for medical and health sciences librarians. For those professionals who provide reference and public services to health sciences personnel in clinical, educational, or research settings, Medical Reference Services Quarterly covers topics of current interest and practical value in the areas of reference in medicine and related specialties, the biomedical sciences, nursing, and allied health. This exciting and comprehensive resource regularly publishes brief practice-oriented articles relating to medical reference services, with an emphasis on user education, database searching, and electronic information. Two columns feature the Internet and informatics education.
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