参考文献/References:
[1].American College of Cardiology Foundation Appropriate Use Criteria Task Force, American Society of Echocardiography,American Heart Association. ACCF/ASE/AHA/ASNC/HFSA/HRS/SCAI/SCCM/SCCT/SCMR 2011 Appropriate Use Criteria for Echocardiography. A Report of the American College of Cardiology Foundation Appropriate Use Criteria Task Force,American Society of Echocardiography,American Heart Association,American Society of Nuclear Cardiology,Heart Failure Society of America,Heart Rhythm Society,Society for Cardiovascular Angiography and Interventions,Society of Critical Care Medicine,Society of Cardiovascular Computed Tomography,Society for Cardiovascular Magnetic Resonance American College of Chest Physicians[J].?J Am Soc Echocardiogr,2011,24(3):229-267.
[2].Hoffmann?R,Lethen?H,Marwick?T,et al. Analysis of i nterinstitutional observer agreement in interpretation of d obutamine stress echocardiograms[J]. J Am Coll Cardiol,1996,27(2):330-336.
[3].Lee?JG,Jun?S,Cho?YW,et al. Deep learning in medical imaging:general overview[J]. Korean J Radiol,2017,18(4):570-584.
[4].Narula?S,Shameer?K,Salem Omar?AM,et al. Machine-learning algorithms to automate morphological and functional assessments in 2D echocardiography[J]. J Am Coll Cardiol,2016,68(21):2287-2295.
[5].Shameer?K,Johnson?KW,Glicksberg?BS,et al. Machine learning in cardiovascular medicine:are we there yet?[J] Heart,2018,104(14):1156-1164.
[6].Fatima?M,Pasha?M. Survey of machine learning algorithms for disease diagnostic[J]. JILSA,2017,9(1):1-16.
[7].Cabitza?F,Rasoini?R,Gensini?GF,et al. Unintended consequences of machine learning in medicine[J]. JAMA,2017,318(6):517-518.
[8].Wolterink?JM,Leiner?T,Takx?RAP,et al. Automatic coronary calcium scoring in non-contrast-enhanced ECG-triggered cardiac CT with ambiguity detection[J]. IEEE Trans Med Imaging,2015,34(9):1867-1878.
[9].Kooi T,Litjens G,van Ginneken B,et al. Large scale deep learning for computer aided detection of mammographic lesions[J]. Med Image Anal,2017,35:303-312.
[10].Esteva?A,Kuprel?B,Novoa?RA,et al. Dermatologist-level classification of skin cancer with deep neural networks[J]. Nature,2017,542(7639):115-118.
[11].Lang RM,Badano LP,Mor-Avi V,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[J]. Eur Heart J Cardiovasc Imaging,2015,16(3):233-270.
[12].Sengupta PP ,Adjeroh DA. Will artificial intelligence replace the human echocardiographer?[J] Circulation,2018,138(16):1639-1642.
[13].DeCara?JM,Lang?RM,Koch?R,et al. The use of small personal ultrasound devices by internists without formal training in echocardiography[J]. Eur J Echocardiogr,2003,4(2):141-147.
[14].Johnson KW,Soto JT,Glicksberg BS,et al. Artificial intelligence in cardiology[J]. J Am Coll Cardiol,2018,71(23):2668-2679.
[15].Levy F,Schouver ED,Iacuzio L,et al. Performance of new automated transthoracic three-dimensional echocardiographic software for left ventricular volumes and function assessment in routine clinical practice:comparison with 3??Tesla cardiac magnetic resonance[J]. Arch Cardiovasc Dis,2017,110(11):580-589.
[16].Krittanawong C,Tunhasiriwet A,Zhang HJ,et al. Deep learning with unsupervised feature in echocardiographic imaging[J]. J Am Coll Cardiol,2017,69(16):2100-2101.
[17].Khamis H,Zurakhov G,Azar V,et al. Automatic apical view classification of echocardiograms using a discriminative learning dictionary[J]. Med Image Anal,2017,36:15-21.
[18].Abdi AH,Luong C,Tsang T,et al. Automatic quality assessment of echocardiograms using convolutional neural networks:feasibility on the apical four-chamber view[J]. IEEE Trans Med Imaging,2017,36(6):1221-1230.
[19].Madani A,Arnaout R,Mofrad M,et al. Fast and accurate classification of echocardiograms using deep learning[J]. NPJ Digit Med,2018,1:6.
[20].Zhou SK. Shape regression machine and efficient segmentation of left ventricle endocardium from 2D B-mode echocardiogram[J]. Med Image Anal,2010,14(4): 563-581.
[21].Cannesson M,Tanabe M,Suffoletto MS,et al. A novel two-dimensional echocardiographic image analysis system using artificial intelligence-learned pattern recognition for rapid automated ejection fraction[J]. J Am Coll Cardiol, 2007,49(2):217-226.
[22].Knackstedt C,Bekkers SCAM,Schummers G,et al. Fully automated versus standard tracking of left ventricular ejection fraction and longitudinal strain[J]. J Am Coll Cardiol,2015,66(13):1456-1466.
[23].Tsang W,Salgo IS,Medvedofsky D,et al. Transthoracic 3D echocardiographic left heart chamber quantification using an automated adaptive analytics algorithm[J]. JACC Cardiovasc Imaging,2016,9(7):769-782.
[24].Narang A,Mor-Avi V,Prado A,et al. Machine learning based automated dynamic quantification of left heart chamber volumes[J]. Eur Heart J Cardiovasc Imaging,2019,20(5):541-549.
[25].Volpato V,Mor-Avi V,Narang A,et al. Automated,machine learning-based,3D echocardiographic quantification of left ventricular mass[J]. Echocardiography, 2019,36(2):312-319.
[26].Genovese D,Rashedi N,Weinert L,et al. Machine learning-based three-dimensional echocardiographic quantification of right ventricular size and function:validation against cardiac magnetic resonance[J]. J Am Soc Echocardiogr, 2019,32(8):969-977.
[27].Zoghbi WA,Adams D,Bonow RO,et al. Recommendations for noninvasive evaluation of native valvular regurgitation[J]. J Am Soc Echocardiogr,2017,30(4):303-371.
[28].Thavendiranathan P,Liu S,Datta S,et al. Quantification of chronic functional mitral regurgitation by automated 3-dimensional peak and integrated proximal isovelocity surface area and stroke volume techniques using real-time 3-dimensional volume color Doppler echocardiography:in vitro and clinical validation[J]. Circ Cardiovasc Imaging,2013,6(1):125-133.
[29].de Agustín JA ,Marcos-Alberca P,Fernandez-Golfin C,et al. Direct measurement of proximal isovelocity surface area by single-beat three-dimensional color Doppler echocardiography in mitral regurgitation:a validation study[J]. J Am Soc Echocardiogr,2012,25(8):815-823.
[30].Choi J,Hong GR,Kim M,et al. Automatic quantification of aortic aegurgitation using 3D full volume color doppler echocardiography:a validation study with cardiac magnetic resonance imaging[J]. Int J Cardiovasc Imaging,2015,31(7):1379-1389.
[31].Jeganathan J,Knio Z,Amador Y,et al. Artificial intelligence in mitral valve analysis[J]. Ann Card Anaesth,2017,20(2):129-134.
[32].陈丽君. 超声心动图评价肥厚型心肌病进展[J]. 心血管病学进展,2017,22(2): 1004-3934.
[33].Narula?S,Shameer?K,Salem Omar?AM,et al. Machine-learning algorithms to automate morphological and functional assessments in 2D echocardiography[J]. J Am Coll Cardiol,2016,68(21):2287-2295.
[34].Mahmoud A,Bansal M,Sengupta PP. New cardiac imaging algorithms to diagnose constrictive pericarditis versus restrictive cardiomyopathy[J]. Curr Cardiol Rep,2017,19(5):43.
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