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Adequacy and Effectiveness of Watson For Oncology in the Treatment of Thyroid Carcinoma

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dc.contributor.author김수영-
dc.contributor.author김희준-
dc.contributor.author박정수-
dc.contributor.author윤혁준-
dc.contributor.author이용상-
dc.contributor.author장항석-
dc.date.accessioned2021-09-29T02:01:37Z-
dc.date.available2021-09-29T02:01:37Z-
dc.date.issued2021-03-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/184672-
dc.description.abstractackground: IBM's Watson for Oncology (WFO) is an artificial intelligence tool that trains by acquiring data from the Memorial Sloan Kettering Cancer Center and learns from test cases and experts. This study aimed to analyze the adequacy and effectiveness of WFO in determining the treatment method for patients with thyroid carcinoma. Materials and methods: We retrospectively enrolled 50 patients with thyroid cancer who underwent surgery in 2018 and entered their clinical data into WFO. The WFO treatment recommendations were compared with the surgical procedures and recommended treatments performed according to the Korean Thyroid Endocrine Surgery Association guidelines. Results: The overall concordance rate between WFO-recommended treatments and actual surgical treatments was 48%, and for patients with stage I, II, and III disease, these rates were 52.4, 50, and 16.7%, respectively. A lower concordance rate was observed with respect to treatment for advanced thyroid cancer. Conclusion: WFO is a useful clinical aid but must be used with caution. A surgeon's decision takes precedence over WFO recommendations in the treatment of advanced thyroid cancer.-
dc.description.statementOfResponsibilityopen-
dc.formatapplication/pdf-
dc.languageEnglish-
dc.publisherFrontiers Research-
dc.relation.isPartOfFRONTIERS IN ENDOCRINOLOGY-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.titleAdequacy and Effectiveness of Watson For Oncology in the Treatment of Thyroid Carcinoma-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Surgery (외과학교실)-
dc.contributor.googleauthorHyeok Jun Yun-
dc.contributor.googleauthorHee Jun Kim-
dc.contributor.googleauthorSoo Young Kim-
dc.contributor.googleauthorYong Sang Lee-
dc.contributor.googleauthorChi Young Lim-
dc.contributor.googleauthorHang-Seok Chang-
dc.contributor.googleauthorCheong Soo Park-
dc.identifier.doi10.3389/fendo.2021.585364-
dc.contributor.localIdA04725-
dc.contributor.localIdA05236-
dc.contributor.localIdA01646-
dc.contributor.localIdA06022-
dc.contributor.localIdA02978-
dc.contributor.localIdA03488-
dc.relation.journalcodeJ03412-
dc.identifier.eissn1664-2392-
dc.identifier.pmid33746898-
dc.subject.keywordIBM-
dc.subject.keywordWatson for Oncology-
dc.subject.keywordartificial intelligence-
dc.subject.keywordthyroid cancer-
dc.subject.keywordtreatment recommendation-
dc.contributor.alternativeNameKim, Soo Young-
dc.contributor.affiliatedAuthor김수영-
dc.contributor.affiliatedAuthor김희준-
dc.contributor.affiliatedAuthor박정수-
dc.contributor.affiliatedAuthor윤혁준-
dc.contributor.affiliatedAuthor이용상-
dc.contributor.affiliatedAuthor장항석-
dc.citation.volume12-
dc.citation.startPage585364-
dc.identifier.bibliographicCitationFRONTIERS IN ENDOCRINOLOGY, Vol.12 : 585364, 2021-03-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Surgery (외과학교실) > 1. Journal Papers

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