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Sekiguchi M, Hiroe M, Take M, Hirosawa K. Clinical and histopathological profile of sarcoidosis of the heart and acute idiopathic myocarditis. Concepts through a study employing endomyocardial biopsy. II: Myocarditis. <i>Jpn Circ J<\/i> 1980; 44: 264\u2013273.","DOI":"10.1253\/jcj.44.264"},{"key":"2","doi-asserted-by":"crossref","unstructured":"2. Roberts WC, McAllister HA Jr, Ferrans VJ. Sarcoidosis of the heart: A clinicopathologic study of 35 necropsy patients (Group I) and review of 78 previously described necropsy patients (Group II). <i>Am J Med<\/i> 1977; 63: 86\u2013108.","DOI":"10.1016\/0002-9343(77)90145-0"},{"key":"3","doi-asserted-by":"crossref","unstructured":"3. Kandolin R, Lehtonen J, Airaksinen J, Vihinen T, Miettinen H, Ylitalo K, et al. Cardiac sarcoidosis: Epidemiology, characteristics, and outcome over 25 years in a nationwide study. <i>Circulation<\/i> 2015; 131: 624\u2013632.","DOI":"10.1161\/CIRCULATIONAHA.114.011522"},{"key":"4","doi-asserted-by":"crossref","unstructured":"4. Birnie DH, Sauer WH, Bogun F, Cooper JM, Culver DA, Duvernoy CS, et al. HRS expert consensus statement on the diagnosis and management of arrhythmias associated with cardiac sarcoidosis. <i>Heart Rhythm<\/i> 2014; 11: 1304\u20131323.","DOI":"10.1016\/j.hrthm.2014.03.043"},{"key":"5","doi-asserted-by":"crossref","unstructured":"5. Terasaki F, Azuma A, Anzai T, Ishizaka N, Ishida Y, Isobe M, et al; on behalf of the Japanese Circulation Society Joint Working Group. JCS 2016 guideline on diagnosis and treatment of cardiac sarcoidosis: Digest version. <i>Circ J<\/i> 2019; 83: 2329\u20132388.","DOI":"10.1253\/circj.CJ-19-0508"},{"key":"6","doi-asserted-by":"crossref","unstructured":"6. Kusano KF, Satomi K. Diagnosis and treatment of cardiac sarcoidosis. <i>Heart<\/i> 2016; 102: 184\u2013190.","DOI":"10.1136\/heartjnl-2015-307877"},{"key":"7","unstructured":"7. Satou M, Shishido H, Satou S, Iwata Y, Ooki K, Kondou E, et al. A hard case to diagnose: Cardiac sarcoidosis. <i>Med J Asahikawa RCH<\/i> 2014; 28: 25\u201330."},{"key":"8","doi-asserted-by":"crossref","unstructured":"8. Lecun Y, Bengio Y, Hinton G. Deep learning. <i>Nature<\/i> 2015; 521: 436\u2013444.","DOI":"10.1038\/nature14539"},{"key":"9","doi-asserted-by":"crossref","unstructured":"9. Zhang J, Gajjala S, Agrawal P, Tison GH, Hallock LA, Beussink-Nelson L, et al. Fully automated echocardiogram interpretation in clinical practice: Feasibility and diagnostic accuracy. <i>Circulation<\/i> 2018; 138: 1623\u20131635.","DOI":"10.1161\/CIRCULATIONAHA.118.034338"},{"key":"10","doi-asserted-by":"crossref","unstructured":"10. Ouyang D, He B, Ghorbani A, Yuan N, Ebinger J, Langlotz CP, et al. Video-based AI for beat-to-beat assessment of cardiac function. <i>Nature<\/i> 2020; 580: 252\u2013256.","DOI":"10.1038\/s41586-020-2145-8"},{"key":"11","doi-asserted-by":"crossref","unstructured":"11. Shin HC, Roth HR, Gao M, Lu L, Xu Z, Nogues I, et al. Deep convolutional neural networks for computer-aided detection: CNN architectures, dataset characteristics and transfer learning. <i>IEEE Trans Med Imaging<\/i> 2016; 35: 1285\u20131298.","DOI":"10.1109\/TMI.2016.2528162"},{"key":"12","doi-asserted-by":"crossref","unstructured":"12. Chan HP, Samala RK, Hadjiiski LM, Zhou C. Deep learning in medical image analysis. <i>Adv Exp Med Biol<\/i> 2020; 1213: 3\u201321.","DOI":"10.1007\/978-3-030-33128-3_1"},{"key":"13","doi-asserted-by":"crossref","unstructured":"13. Lang RM, Badano LP, Victor MA, Afilalo J, Armstrong A, Ernande L, et al. Recommendations for cardiac chamber quantification by echocardiography in adults: An update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging. <i>J Am Soc Echocardiogr<\/i> 2015; 28: 1\u201339.e14.","DOI":"10.1016\/j.echo.2014.10.003"},{"key":"14","doi-asserted-by":"crossref","unstructured":"14. Tran D, Wang H, Torresani L, Ray J, Lecun Y, Paluri M. A closer look at spatiotemporal convolutions for action recognition. arXiv:1711.11248v3 [cs.CV], 2018. https:\/\/arxiv.org\/abs\/1711.11248v3.","DOI":"10.1109\/CVPR.2018.00675"},{"key":"15","unstructured":"15. Kingma DP, Ba JL. Adam: A method for stochastic optimization. <i>In<\/i>: Bengio Y, LeCun Y, editors. ICLR 2015 Conference Track Proceedings [Proceedings of the 3rd International Conference on Learning Representations], 7\u20139 May 2015, San Diego, CA, USA."},{"key":"16","doi-asserted-by":"crossref","unstructured":"16. Gotkowski K, Gonzalez C, Bucher A, Mukhopadhyay A. M3d-CAM: A PyTorch library to generate 3D data attention maps for medical deep learning. arXiv:2007.00453 [cs.CV], 2020. https:\/\/arxiv.org\/abs\/2007.00453 (accessed June 2021).","DOI":"10.1007\/978-3-658-33198-6_52"},{"key":"17","doi-asserted-by":"crossref","unstructured":"17. Carpenter J, Bithell J. Bootstrap confidence intervals: When, which, what?: A practical guide for medical statisticians. <i>Stat Med<\/i> 2000; 19: 1141\u20131164.","DOI":"10.1002\/(SICI)1097-0258(20000515)19:9<1141::AID-SIM479>3.0.CO;2-F"},{"key":"18","doi-asserted-by":"crossref","unstructured":"18. Delong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: A nonparametric approach. <i>Biometrics<\/i> 2016; 44: 837\u2013845.","DOI":"10.2307\/2531595"},{"key":"19","unstructured":"19. Lemley J, Bazrafkan S, Corcoran P. Transfer learning of temporal information for driver action classification. <i>In<\/i>: Proceedings of 28th Modern Artificial Intelligence and Cognitive Science Conference, Fort Wayne, IN, April 2017; 123\u2013128."},{"key":"20","doi-asserted-by":"crossref","unstructured":"20. Rajpurkar P, Irvin J, Ball RL, Zhu K, Yang B, Mehta H, et al. Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists. <i>PLoS Med<\/i> 2018; 15: 1\u201317.","DOI":"10.1371\/journal.pmed.1002686"},{"key":"21","doi-asserted-by":"crossref","unstructured":"21. Rajpurkar P, Park A, Irvin J, Chute C, Bereket M, Mastrodicasa D, et al. AppendiXNet: Deep learning for diagnosis of appendicitis from a small dataset of CT exams using video pretraining. <i>Sci Rep<\/i> 2020; 10: 1\u20137.","DOI":"10.1038\/s41598-020-61055-6"},{"key":"22","doi-asserted-by":"crossref","unstructured":"22. Kurmann R, Mankad SV, Mankad R. Echocardiography in sarcoidosis. <i>Curr Cardiol Rep<\/i> 2018; 20: 118.","DOI":"10.1007\/s11886-018-1065-9"},{"key":"23","doi-asserted-by":"crossref","unstructured":"23. Kheradvar A, Gharib M. On mitral valve dynamics and its connection to early diastolic flow. <i>Ann Biomed Eng<\/i> 2009; 37: 1\u201313.","DOI":"10.1007\/s10439-008-9588-7"},{"key":"24","doi-asserted-by":"crossref","unstructured":"24. Sayah DM, Bradfield JS, Moriarty JM, Belperio JA, Lynch JP. Cardiac involvement in sarcoidosis: Evolving concepts in diagnosis and treatment. <i>Semin Respir Crit Care Med<\/i> 2017; 38: 477\u2013498.","DOI":"10.1055\/s-0037-1602381"},{"key":"25","doi-asserted-by":"crossref","unstructured":"25. Otsuji Y, Gilon D, Jiang L, He S, Leavitt M, Roy MJ, et al. Restricted diastolic opening of the mitral leaflets in patients with left ventricular dysfunction: Evidence for increased valve tethering. <i>J Am Coll Cardiol<\/i> 1998; 32: 398\u2013404.","DOI":"10.1016\/S0735-1097(98)00237-X"},{"key":"26","doi-asserted-by":"crossref","unstructured":"26. Burstow DJ, Tajik AJ, Bailey KR, DeRemee RA, Taliercio CP. Two-dimensional echocardiographic findings in systemic sarcoidosis. <i>Am J Cardiol<\/i> 1989; 63: 478\u2013482.","DOI":"10.1016\/0002-9149(89)90323-8"},{"key":"27","doi-asserted-by":"crossref","unstructured":"27. Freeman AM, Curran-Everett D, Weinberger HD, Fenster BE, Buckner JK, Gottschall EB, et al. 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