Su Hwan Kim, Severin Schramm, Lisa C. Adams, Rickmer Braren, Keno K. Bressem, Matthias Keicher, Claus Zimmer, Dennis M. Hedderich, Benedikt Wiestler
{"title":"开放源码 LLM 在具有挑战性的放射病例中的表现--对 4,049 份 Eurorad 病例报告的基准研究","authors":"Su Hwan Kim, Severin Schramm, Lisa C. Adams, Rickmer Braren, Keno K. Bressem, Matthias Keicher, Claus Zimmer, Dennis M. Hedderich, Benedikt Wiestler","doi":"10.1101/2024.09.04.24313026","DOIUrl":null,"url":null,"abstract":"<strong>Background</strong> Recent advancements in large language models (LLMs) have created new ways to support radiological diagnostics. While both open-source and proprietary LLMs can address privacy concerns through local or cloud deployment, open-source models provide advantages in continuity of access, independence from commercial update cycles, and potentially lower costs.","PeriodicalId":501358,"journal":{"name":"medRxiv - Radiology and Imaging","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Performance of Open-Source LLMs in Challenging Radiological Cases – A Benchmark Study on 4,049 Eurorad Case Reports\",\"authors\":\"Su Hwan Kim, Severin Schramm, Lisa C. Adams, Rickmer Braren, Keno K. Bressem, Matthias Keicher, Claus Zimmer, Dennis M. Hedderich, Benedikt Wiestler\",\"doi\":\"10.1101/2024.09.04.24313026\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<strong>Background</strong> Recent advancements in large language models (LLMs) have created new ways to support radiological diagnostics. While both open-source and proprietary LLMs can address privacy concerns through local or cloud deployment, open-source models provide advantages in continuity of access, independence from commercial update cycles, and potentially lower costs.\",\"PeriodicalId\":501358,\"journal\":{\"name\":\"medRxiv - Radiology and Imaging\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"medRxiv - Radiology and Imaging\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1101/2024.09.04.24313026\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv - Radiology and Imaging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.09.04.24313026","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Performance of Open-Source LLMs in Challenging Radiological Cases – A Benchmark Study on 4,049 Eurorad Case Reports
Background Recent advancements in large language models (LLMs) have created new ways to support radiological diagnostics. While both open-source and proprietary LLMs can address privacy concerns through local or cloud deployment, open-source models provide advantages in continuity of access, independence from commercial update cycles, and potentially lower costs.
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