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人工智能在心脏影像诊断中的研究进展(5)
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摘要:[40] Betancur J,Commandeur F,Motlagh M,et al.Deep learning for prediction of obstructive disease from fast myocardial perfusion SPECT:a multicenter study[J]. JACC Cardiovasc Imaging, 2018, 11: 1654-16
[40] Betancur J,Commandeur F,Motlagh M,et al.Deep learning for prediction of obstructive disease from fast myocardial perfusion SPECT:a multicenter study[J]. JACC Cardiovasc Imaging, 2018, 11: 1654-1663.
[41] Betancur J,Otaki Y,Motwani M,et value of combined clinical and myocardial perfusion imaging data using machine learning[J].JACC Cardiovasc Imaging,2018,11:1000-1009.
[42] Arsanjani R, Dey D, Khachatryan T, et of revascularization after myocardial perfusion SPECT by machine learning in a large population[J].J Nucl Cardiol,2015,22:877-884.
[43] Dey D,Diaz Zamudio M,Schuhbaeck A, et between quantitative adverse plaque features from coronary computed tomography angiography and downstream impaired myocardial flow reserve by13N-ammonia positron emission tomography: a pilot study[J].Circ Cardiovasc Imaging,2015,8:e003255.
[44] Siegersma KR, Leiner T, Chew DP, et intelligence in cardiovascular imaging: state of the art and implications for the imaging cardiologist[J].Neth Heart J,2019,27:403-413.
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