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대형 언어 모델: 영상의학 전문가를 위한 종합 안내서

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dc.contributor.author김승섭-
dc.contributor.author이충근-
dc.date.accessioned2024-12-06T02:38:46Z-
dc.date.available2024-12-06T02:38:46Z-
dc.date.issued2024-09-
dc.identifier.issn1738-2637-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/200860-
dc.description.abstractLarge language models (LLMs) have revolutionized the global landscape of technology beyond natural language processing. Owing to their extensive pre-training on vast datasets, contemporary LLMs can handle tasks ranging from general functionalities to domain-specific areas, such as radiology, without additional fine-tuning. General-purpose chatbots based on LLMs can optimize the efficiency of radiologists in terms of their professional work and research endeavors. Importantly, these LLMs are on a trajectory of rapid evolution, wherein challenges such as “hallucination,” high training cost, and efficiency issues are addressed, along with the inclusion of multimodal inputs. In this review, we aim to offer conceptual knowledge and actionable guidance to radiologists interested in utilizing LLMs through a succinct overview of the topic and a summary of radiology-specific aspects, from the beginning to potential future directions.-
dc.description.statementOfResponsibilityopen-
dc.languageKorean-
dc.publisher대한영상의학회-
dc.relation.isPartOfJournal of the Korean Society of Radiology(대한영상의학회지)-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.title대형 언어 모델: 영상의학 전문가를 위한 종합 안내서-
dc.title.alternativeLarge Language Models: A Comprehensive Guide for Radiologists-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Radiology (영상의학교실)-
dc.contributor.googleauthor김선규-
dc.contributor.googleauthor이충근-
dc.contributor.googleauthor김승섭-
dc.identifier.doi10.3348/jksr.2024.0080-
dc.contributor.localIdA05097-
dc.contributor.localIdA03259-
dc.relation.journalcodeJ01843-
dc.identifier.eissn2288-2928-
dc.subject.keywordNatural Language Processing-
dc.subject.keywordLarge Language Model-
dc.subject.keywordTransformer-
dc.subject.keywordRadiology-
dc.subject.keywordChatbot-
dc.subject.keywordChatGPT-
dc.contributor.alternativeNameKim, Seung-seob-
dc.contributor.affiliatedAuthor김승섭-
dc.contributor.affiliatedAuthor이충근-
dc.citation.volume85-
dc.citation.number5-
dc.citation.startPage861-
dc.citation.endPage882-
dc.identifier.bibliographicCitationJournal of the Korean Society of Radiology (대한영상의학회지), Vol.85(5) : 861-882, 2024-09-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Internal Medicine (내과학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers

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