Machine learning assessment of myocardial ischemia using angiography: Development and retrospective validation
by Hyeonyong Hae, Soo-Jin Kang, Won-Jang Kim, So-Yeon Choi, June-Goo Lee, Youngoh Bae, Hyungjoo Cho, Dong Hyun Yang, Joon-Won Kang, Tae-Hwan Lim, Cheol Hyun Lee, Do-Yoon Kang, Pil Hyung Lee, Jung-Min Ahn, Duk-Woo Park, Seung-Whan Lee, Young-Hak Kim, Cheol Whan Lee, Seong-Wook Park, Seung-Jung Park
BackgroundInvasive fractional flow reserve (FFR) is a standard tool for identifying ischemia-producing coronary stenosis. However, in clinical practice, over 70% of treatment decisions still rely on visual estimation of angiographic stenosis, which has limited accuracy (about 60% –65%) for the prediction of FFR
Source: PLoS Medicine - Category: Internal Medicine Authors: Hyeonyong Hae Source Type: research