{"title":"长冠状病毒和大语言模型时代的知识表示与管理：2022-2023年调查。","authors":"Jonathan P Bona","doi":"10.1055/s-0044-1800747","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>To select, present, and summarize cutting edge work in the field of Knowledge Representation and Management (KRM) published in 2022 and 2023.</p><p><strong>Methods: </strong>A comprehensive set of KRM-relevant articles published in 2022 and 2023 was retrieved by querying PubMed. Topic modeling with Latent Dirichlet Allocation was used to further refine this query and suggest areas of focus. Selected articles were chosen based on a review of their title and abstract.</p><p><strong>Results: </strong>An initial set of 8,706 publications were retrieved from PubMed. From these, fifteen papers were ultimately selected matching one of two main themes: KRM for long COVID, and KRM approaches used in combination with generative large language models.</p><p><strong>Conclusions: </strong>This survey shows the ongoing development and versatility of KRM approaches, both to improve our understanding of a global health crisis and to augment and evaluate cutting edge technologies from other areas of artificial intelligence.</p>","PeriodicalId":40027,"journal":{"name":"Yearbook of medical informatics","volume":"33 1","pages":"216-222"},"PeriodicalIF":0.0000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12020515/pdf/","citationCount":"0","resultStr":"{\"title\":\"Knowledge Representation and Management in the Age of Long Covid and Large Language Models: a 2022-2023 Survey.\",\"authors\":\"Jonathan P Bona\",\"doi\":\"10.1055/s-0044-1800747\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objectives: </strong>To select, present, and summarize cutting edge work in the field of Knowledge Representation and Management (KRM) published in 2022 and 2023.</p><p><strong>Methods: </strong>A comprehensive set of KRM-relevant articles published in 2022 and 2023 was retrieved by querying PubMed. Topic modeling with Latent Dirichlet Allocation was used to further refine this query and suggest areas of focus. Selected articles were chosen based on a review of their title and abstract.</p><p><strong>Results: </strong>An initial set of 8,706 publications were retrieved from PubMed. From these, fifteen papers were ultimately selected matching one of two main themes: KRM for long COVID, and KRM approaches used in combination with generative large language models.</p><p><strong>Conclusions: </strong>This survey shows the ongoing development and versatility of KRM approaches, both to improve our understanding of a global health crisis and to augment and evaluate cutting edge technologies from other areas of artificial intelligence.</p>\",\"PeriodicalId\":40027,\"journal\":{\"name\":\"Yearbook of medical informatics\",\"volume\":\"33 1\",\"pages\":\"216-222\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12020515/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Yearbook of medical informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1055/s-0044-1800747\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/4/8 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Yearbook of medical informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1055/s-0044-1800747","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/4/8 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
Knowledge Representation and Management in the Age of Long Covid and Large Language Models: a 2022-2023 Survey.
Objectives: To select, present, and summarize cutting edge work in the field of Knowledge Representation and Management (KRM) published in 2022 and 2023.
Methods: A comprehensive set of KRM-relevant articles published in 2022 and 2023 was retrieved by querying PubMed. Topic modeling with Latent Dirichlet Allocation was used to further refine this query and suggest areas of focus. Selected articles were chosen based on a review of their title and abstract.
Results: An initial set of 8,706 publications were retrieved from PubMed. From these, fifteen papers were ultimately selected matching one of two main themes: KRM for long COVID, and KRM approaches used in combination with generative large language models.
Conclusions: This survey shows the ongoing development and versatility of KRM approaches, both to improve our understanding of a global health crisis and to augment and evaluate cutting edge technologies from other areas of artificial intelligence.
期刊介绍：
Published by the International Medical Informatics Association, this annual publication includes the best papers in medical informatics from around the world.
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