文献

J-GLOBAL ID：201902238215498326   整理番号：19A2004129

機械学習アルゴリズムを用いたオンサイトコンピュータ断層撮影による冠血流予備量比-後ろ向き多施設コホートにおける臨床有効性-

On-Site Computed Tomography-Derived Fractional Flow Reserve Using a Machine-Learning Algorithm - Clinical Effectiveness in a Retrospective Multicenter Cohort -

著者 (18件)： Kurata Akira (Department of Radiology, Ehime University Graduate School of Medicine) ,  Fukuyama Naoki (Department of Radiology, Ehime University Graduate School of Medicine) ,  Fukuyama Naoki (Department of Radiology, Ehime Prefectural Central Hospital) ,  Hirai Kuniaki (Department of Radiology, Ehime University Graduate School of Medicine) ,  Hirai Kuniaki (Department of Radiology, Saiseikai-Matsuyama Hospital) ,  Kawaguchi Naoto (Department of Radiology, Ehime University Graduate School of Medicine) ,  Kawaguchi Naoto (Department of Radiology, Ehime Prefectural Central Hospital) ,  Tanabe Yuki (Department of Radiology, Ehime University Graduate School of Medicine) ,  Okayama Hideki (Department of Cardiology, Ehime Prefectural Central Hospital) ,  Shigemi Susumu (Department of Cardiology, Saiseikai-Matsuyama Hospital) ,  Watanabe Kouki (Department of Cardiology, Saiseikai-Matsuyama Hospital) ,  Uetani Teruyoshi (Department of Cardiology, Pulmonology, Hypertension & Nephrology, Ehime University Graduate School of Medicine) ,  Ikeda Shuntaro (Department of Cardiology, Pulmonology, Hypertension & Nephrology, Ehime University Graduate School of Medicine) ,  Inaba Shinji (Department of Cardiology, Kitaishikai Hospital) ,  Kido Teruhito (Department of Radiology, Ehime University Graduate School of Medicine) ,  Itoh Toshihide (Research and Collaboration, Siemens Healthcare) ,  Mochizuki Teruhito (Department of Radiology, Ehime University Graduate School of Medicine) ,  Mochizuki Teruhito (Department of Radiology, I.M. Sechenov First Moscow State Medical University)
資料名： Circulation Journal  (Circulation Journal)
巻： 83  号： 7  ページ： 1563-1571(J-STAGE)  発行年： 2019年 
JST資料番号： F0908A  ISSN： 1346-9843  資料種別： 逐次刊行物 (A)
記事区分： 原著論文  発行国： 日本 (JPN)  言語： 英語 (EN)

抄録/ポイント： 背景:本研究は,侵襲性冠血流予備量比(FFR)により評価した...

シソーラス用語： *冠動脈疾患 ,...
準シソーラス用語： *冠血流予備量比 ,...

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著者キーワード (5件)： 人工知能 ,  コンピュータ断層撮影 ,  冠動脈疾患 ,  フラクショナルフロー予備量 ,  機械学習

分類 (1件)： 循環系の診断  (GJ02000V)

引用文献 (35件)：

• 1. Yamagishi M, Tamaki N, Akasaka T, Ikeda T, Uemura S, Otsuji Y, et al. JCS 2018 guideline on diagnosis of chronic coronary heart diseases (in Japanese). http://www.j-circ.or.jp/guideline/pdf/JCS2018_yamagishi_tamaki.pdf (accessed March 2019).
• 2. Wolk MJ, Bailey SR, Doherty JU, Douglas PS, Hendel RC, Kramer CM, et al. ACCF/AHA/ASE/ASNC/HFSA/HRS/SCAI/SCCT/SCMR/STS 2013 multimodality appropriate use criteria for the detection and risk assessment of stable ischemic heart disease: A report of the American College of Cardiology Foundation Appropriate Use Criteria Task Force, American Heart Association, American Society of Echocardiography, American Society of Nuclear Cardiology, Heart Failure Society of America, Heart Rhythm Society, Society for Cardiovascular Angiography and Interventions, Society of Cardiovascular Computed Tomography, Society for Cardiovascular Magnetic Resonance, and Society of Thoracic Surgeons. J Am Coll Cardiol 2014; 63: 380-406.
• 3. Di Carli MF, Murthy VL. Cardiac PET/CT for the evaluation of known or suspected coronary artery disease. Radiographics 2011; 31: 1239-1254.
• 4. Cury RC, Abbara S, Achenbach S, Agatston A, Berman DS, Budoff MJ, et al. CAD-RADS(TM) Coronary Artery Disease: Reporting and Data System. An expert consensus document of the Society of Cardiovascular Computed Tomography (SCCT), the American College of Radiology (ACR) and the North American Society for Cardiovascular Imaging (NASCI). Endorsed by the American College of Cardiology. J Cardiovasc Comput Tomogr 2016; 10: 269-281.
• 5. Pijls NH, De Bruyne B, Peels K, Van Der Voort PH, Bonnier HJ, Bartunek J, et al. Measurement of fractional flow reserve to assess the functional severity of coronary-artery stenoses. N Engl J Med 1996; 334: 1703-1708.

タイトルに関連する用語 (8件)： 機械学習 ,  アルゴリズム ,  コンピュータ断層撮影 ,  冠血流予備量比 ,  施設 ,  コホート ,  臨床 ,  有効性