{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,15]],"date-time":"2025-08-15T01:03:50Z","timestamp":1755219830290,"version":"3.43.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686080","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T00:00:00Z","timestamp":1754524800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,8,7]]},"abstract":"<jats:p>Dictionaries are essential in natural language processing and provide significant value across tasks; however, their construction and maintenance are expensive. Leveraging manual revision histories to suggest automatic corrections for unedited terms offers a promising solution to enhance quality while reducing costs. This study proposes a method for automatically correcting metadata in a large-scale medical dictionary containing more than 500,000 terms. By utilizing large language models that excel in zero-shot settings, the system estimates the dictionary information without task-specific configurations. This method was demonstrated through experiments on variations in gene biomarker expression, a task that requires specialized medical knowledge. The results indicate that this approach can significantly reduce the dictionary maintenance burden.<\/jats:p>","DOI":"10.3233\/shti250951","type":"book-chapter","created":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:36:08Z","timestamp":1754566568000},"source":"Crossref","is-referenced-by-count":0,"title":["Efficient Maintenance of Large-Scale Medical Dictionaries Using Large Language Models: A Case for Biomarkers"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-0272-4111","authenticated-orcid":false,"given":"Yuka","family":"Otsuki","sequence":"first","affiliation":[{"name":"Nara Institute of Science and Technology, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuntaro","family":"Yada","sequence":"additional","affiliation":[{"name":"Nara Institute of Science and Technology, Japan"},{"name":"University of Tsukuba, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tomohiro","family":"Nishiyama","sequence":"additional","affiliation":[{"name":"Nara Institute of Science and Technology, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Toshiyuki","family":"Sakurai","sequence":"additional","affiliation":[{"name":"Prime Research Institute for Medical RWD, Inc., Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Masafumi","family":"Okada","sequence":"additional","affiliation":[{"name":"Prime Research Institute for Medical RWD, Inc., Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Noriko","family":"Kudo","sequence":"additional","affiliation":[{"name":"Nara Institute of Science and Technology, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kyoko","family":"Kawabata","sequence":"additional","affiliation":[{"name":"Nara Institute of Science and Technology, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Takako","family":"Fujimaki","sequence":"additional","affiliation":[{"name":"Nara Institute of Science and Technology, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hiroyuki","family":"Nagai","sequence":"additional","affiliation":[{"name":"Nara Institute of Science and Technology, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shoko","family":"Wakamiya","sequence":"additional","affiliation":[{"name":"Nara Institute of Science and Technology, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eiji","family":"Aramaki","sequence":"additional","affiliation":[{"name":"Nara Institute of Science and Technology, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","MEDINFO 2025 \u2014 Healthcare Smart \u00d7 Medicine Deep"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI250951","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:36:08Z","timestamp":1754566568000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI250951"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,7]]},"ISBN":["9781643686080"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti250951","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,7]]}}}