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Connection

Roberto M. Lang to Automation

This is a "connection" page, showing publications Roberto M. Lang has written about Automation.
Connection Strength

0.601
  1. Automated Echocardiographic Quantification of Left Ventricular Ejection Fraction Without Volume Measurements Using a Machine Learning Algorithm Mimicking a Human Expert. Circ Cardiovasc Imaging. 2019 09; 12(9):e009303.
    View in: PubMed
    Score: 0.164
  2. Transthoracic 3D Echocardiographic Left Heart Chamber Quantification Using an Automated Adaptive Analytics Algorithm. JACC Cardiovasc Imaging. 2016 07; 9(7):769-782.
    View in: PubMed
    Score: 0.131
  3. Semiautomated detection and quantification of aortic plaques from three-dimensional transesophageal echocardiography. J Am Soc Echocardiogr. 2014 Jul; 27(7):758-66.
    View in: PubMed
    Score: 0.113
  4. Machine learning based quantification of ejection and filling parameters by fully automated dynamic measurement of left ventricular volumes from cardiac magnetic resonance images. Magn Reson Imaging. 2020 04; 67:28-32.
    View in: PubMed
    Score: 0.042
  5. Automated, machine learning-based, 3D echocardiographic quantification of left ventricular mass. Echocardiography. 2019 02; 36(2):312-319.
    View in: PubMed
    Score: 0.039
  6. Three-dimensional echocardiographic quantification of the left-heart chambers using an automated adaptive analytics algorithm: multicentre validation study. Eur Heart J Cardiovasc Imaging. 2018 01 01; 19(1):47-58.
    View in: PubMed
    Score: 0.036
  7. Semi-automated echocardiographic quantification of right ventricular size and function. Int J Cardiovasc Imaging. 2015 Aug; 31(6):1149-57.
    View in: PubMed
    Score: 0.030
  8. Three-dimensional left ventricular segmentation from magnetic resonance imaging for patient-specific modelling purposes. Europace. 2014 Nov; 16 Suppl 4:iv96-iv101.
    View in: PubMed
    Score: 0.029
  9. Automated interpretation of regional left ventricular wall motion from cardiac magnetic resonance images. J Cardiovasc Magn Reson. 2006; 8(3):427-33.
    View in: PubMed
    Score: 0.016
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.