Art
J-GLOBAL ID:201902251063382063   Reference number:19A2041275

Machine learning methods can more efficiently predict prostate cancer compared with prostate-specific antigen density and prostate-specific antigen velocity

前立腺特異抗原密度および前立腺特異抗原速度と比較して前立腺癌をより効率的に予測できる機械学習法【JST・京大機械翻訳】
Author (9):
Material:
Volume:Issue:Page: 114-118  Publication year: 2019 
JST Material Number: W3031A  ISSN: 2287-8882  Document type: Article
Article type: 原著論文  Country of issue: Netherlands (NLD)  Language: ENGLISH (EN)
Abstract/Point:
Abstract/Point
Japanese summary of the article(about several hundred characters).
All summary is available on JDreamIII(charged).
On J-GLOBAL, this item will be available after more than half a year after the record posted. In addtion, medical articles require to login to MyJ-GLOBAL.
Prostate-specific antigen (PSA...
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Thesaurus term:
Thesaurus term/Semi thesaurus term
Keywords indexed to the article.
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Semi thesaurus term:
Thesaurus term/Semi thesaurus term
Keywords indexed to the article.
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, 【Automatic Indexing@JST】
JST classification (1):
JST classification
Category name(code) classified by JST.
Urogenital tumors(=neoplasms) 
Terms in the title (5):
Terms in the title
Keywords automatically extracted from the title.

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