https://scholars.lib.ntu.edu.tw/handle/123456789/557652
標題: | Artificial Intelligence Aids Cardiac Image Quality Assessment for Improving Precision in Strain Measurements | 作者: | KUAN-CHIH HUANG CHIUN-SHENG HUANG MAO-YUAN SU Hung, Chung-Lieh Ethan Tu, Yi-Chin Lin, Lung-Chun HWANG, JUEY-JEN |
關鍵字: | artificial intelligence; automated strain analysis; cancer therapeutics−related cardiac dysfunction; left ventricular global longitudinal strain;artificial intelligence; automated strain analysis; cancer therapeutics?related cardiac dysfunction; left ventricular global longitudinal strain | 公開日期: | 二月-2021 | 卷: | 14 | 期: | 2 | 來源出版物: | JACC. Cardiovascular imaging | 摘要: | The aim of this study was to develop an artificial intelligence tool to assess echocardiographic image quality objectively. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/557652 | ISSN: | 1936878X | DOI: | 10.1016/j.jcmg.2020.08.034 | SDG/關鍵字: | accuracy; adult; Article; artificial intelligence; body mass; breast cancer; cardiovascular magnetic resonance; convolutional neural network; echocardiography; female; follow up; human; image quality; interrater reliability; limit of agreement; major clinical study; male; mastectomy; middle aged; prediction; predictive value; priority journal; test retest reliability; cine magnetic resonance imaging; heart left ventricle function; heart stroke volume; reproducibility; Artificial Intelligence; Humans; Magnetic Resonance Imaging, Cine; Predictive Value of Tests; Reproducibility of Results; Stroke Volume; Ventricular Function, Left |
顯示於: | 醫學院附設醫院 (臺大醫院) |
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