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)： Nitta Satoshi (The Department of Urology, Hitachi General Hospital, Hitachi City, Japan) ,  Tsutsumi Masakazu (The Department of Urology, Hitachi General Hospital, Hitachi City, Japan) ,  Sakka Shotaro (The Department of Urology, Hitachi General Hospital, Hitachi City, Japan) ,  Endo Tsuyoshi (The Department of Urology, Hitachi General Hospital, Hitachi City, Japan) ,  Hashimoto Kenichiro (The Department of Information Systems, Hitachi General Hospital, Hitachi City, Japan) ,  Hasegawa Morikuni (Information and Communication Technology Business Division, Hitachi Ltd., Chiyoda City, Japan) ,  Hayashi Takayuki (Information and Communication Technology Business Division, Hitachi Ltd., Chiyoda City, Japan) ,  Kawai Koji (The Department of Urology, Faculty of Medicine, University of Tsukuba, Tsukuba City, Japan) ,  Nishiyama Hiroyuki (The Department of Urology, Faculty of Medicine, University of Tsukuba, Tsukuba City, Japan)
Material： Prostate International
Volume： 7  Issue： 3  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： Prostate-specific antigen (PSA...

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Thesaurus term： *machine learning ,  *prostatic tumor ,  urine analysis ,  screening(inspection) ,  *prostate-specific antigen ,  neural network(biomodel) ,  statistical model ,  effectiveness ,  support vector machine
Semi thesaurus term： 後向き研究 ,  特異性 ,  ROC曲線 ,  ランダムフォレスト ,  前立腺体積 ,  前立腺生検 , 【Automatic Indexing@JST】

Author keywords (3)： Machine leaning method ,  Prostate cancer ,  Prostate-specific antigen

JST classification (1)： Urogenital tumors(=neoplasms)  (GM04000S)

Terms in the title (5)： 前立腺特異抗原密度 ,  前立腺特異抗原 ,  前立腺癌 ,  予測 ,  機械学習