标题/作者	年份
Artificial intelligence in cardiovascular imaging: JACC state-of-the-art review D Dey, PJ Slomka, P Leeson, D Comaniciu, S Shrestha, PP Sengupta, ... Journal of the American College of Cardiology 73 (11), 1317-1335	2019
Clinical applications of machine learning in cardiovascular disease and its relevance to cardiac imaging SJ Al’Aref, K Anchouche, G Singh, PJ Slomka, KK Kolli, A Kumar, ... European heart journal 40 (24), 1975-1986	2019
State-of-the-art deep learning in cardiovascular image analysis G Litjens, F Ciompi, JM Wolterink, BD de Vos, T Leiner, J Teuwen, I Išgum JACC: Cardiovascular imaging 12 (8 Part 1), 1549-1565	2019
Deep learning for cardiovascular medicine: a practical primer C Krittanawong, KW Johnson, RS Rosenson, Z Wang, M Aydar, U Baber, ... European heart journal 40 (25), 2058-2073	2019
Artificial intelligence for mammography and digital breast tomosynthesis: current concepts and future perspectives KJ Geras, RM Mann, L Moy Radiology 293 (2), 246-259	2019
Machine learning-based coronary artery disease diagnosis: A comprehensive review R Alizadehsani, M Abdar, M Roshanzamir, A Khosravi, PM Kebria, ... Computers in biology and medicine 111, 103346	2019
A deep learning approach for assessment of regional wall motion abnormality from echocardiographic images K Kusunose, T Abe, A Haga, D Fukuda, H Yamada, M Harada, M Sata Cardiovascular Imaging 13 (2_Part_1), 374-381	2020
Artificial intelligence in medical education K Masters Medical Teacher 41 (9), 976-980	2019
Artificial intelligence in cardiology: present and future F Lopez-Jimenez, Z Attia, AM Arruda-Olson, R Carter, ... Mayo Clinic Proceedings 95 (5), 1015-1039	2020
Deep learning in cardiology P Bizopoulos, D Koutsouris IEEE reviews in biomedical engineering 12, 168-193	2018
Deep learning analysis of upright-supine high-efficiency SPECT myocardial perfusion imaging for prediction of obstructive coronary artery disease: a multicenter study J Betancur, LH Hu, F Commandeur, T Sharir, AJ Einstein, MB Fish, ... Journal of Nuclear Medicine 60 (5), 664-670	2019
The promise of artificial intelligence and deep learning in PET and SPECT imaging H Arabi, A AkhavanAllaf, A Sanaat, I Shiri, H Zaidi Physica Medica 83, 122-137	2021
Applications of artificial intelligence and deep learning in molecular imaging and radiotherapy H Arabi, H Zaidi European Journal of Hybrid Imaging 4, 1-23	2020
Proposed requirements for cardiovascular imaging-related machine learning evaluation (PRIME): a checklist: reviewed by the American College of Cardiology Healthcare Innovation Council PP Sengupta, S Shrestha, B Berthon, E Messas, E Donal, GH Tison, ... Cardiovascular Imaging 13 (9), 2017-2035	2020
Recommendations for reporting machine learning analyses in clinical research LM Stevens, BJ Mortazavi, RC Deo, L Curtis, DP Kao Circulation: Cardiovascular Quality and Outcomes 13 (10), e006556	2020
The primary use of artificial intelligence in cardiovascular diseases: what kind of potential role does artificial intelligence play in future medicine? Y Yan, JW Zhang, GY Zang, J Pu Journal of geriatric cardiology: JGC 16 (8), 585	2019
Deep learning–based quantification of epicardial adipose tissue volume and attenuation predicts major adverse cardiovascular events in asymptomatic subjects E Eisenberg, PA McElhinney, F Commandeur, X Chen, S Cadet, ... Circulation: Cardiovascular Imaging 13 (2), e009829	2020
Rationale and design of the RE gistry of F ast Myocardial Perfusion I maging with NE xt generation SPECT (REFINE SPECT) PJ Slomka, J Betancur, JX Liang, Y Otaki, LH Hu, T Sharir, S Dorbala, ... Journal of Nuclear Cardiology 27, 1010-1021	2020
Artificial intelligence in imaging: the radiologist’s role DL Rubin Journal of the American College of Radiology 16 (9), 1309-1317	2019
Data preprocessing for heart disease classification: A systematic literature review H Benhar, A Idri, JL Fernández-Alemán Computer Methods and Programs in Biomedicine 195, 105635	2020

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