Literature DB >> 27884248

Machine Learning for Echocardiographic Imaging: Embarking on Another Incredible Journey.

A Jamil Tajik1.   

Abstract

Keywords:  algorithm; artificial intelligence; computer; hypertrophic cardiomyopathy

Mesh：

Year:  2016        PMID： 27884248     DOI： 10.1016/j.jacc.2016.09.915

Source DB:  PubMed          Journal:  J Am Coll Cardiol        ISSN： 0735-1097            Impact factor:   24.094


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  10 in total

Review 1.  Artificial Intelligence and Machine Learning: A New Disruptive Force in Orthopaedics.

Authors:  Murali Poduval; Avik Ghose; Sanjeev Manchanda; Vaibhav Bagaria; Aniruddha Sinha
Journal:  Indian J Orthop       Date:  2020-01-13       Impact factor: 1.251

Review 2.  Deep learning for cardiac computer-aided diagnosis: benefits, issues & solutions.

Authors:  Brian C S Loh; Patrick H H Then
Journal:  Mhealth       Date:  2017-10-19

3.  A method using deep learning to discover new predictors from left-ventricular mechanical dyssynchrony for CRT response.

Authors:  Zhuo He; Xinwei Zhang; Chen Zhao; Xing Ling; Saurabh Malhotra; Zhiyong Qian; Yao Wang; Xiaofeng Hou; Jiangang Zou; Weihua Zhou
Journal:  J Nucl Cardiol       Date:  2022-08-01       Impact factor: 3.872

4.  Deep Learning for Prediction of Obstructive Disease From Fast Myocardial Perfusion SPECT: A Multicenter Study.

Authors:  Julian Betancur; Frederic Commandeur; Mahsaw Motlagh; Tali Sharir; Andrew J Einstein; Sabahat Bokhari; Mathews B Fish; Terrence D Ruddy; Philipp Kaufmann; Albert J Sinusas; Edward J Miller; Timothy M Bateman; Sharmila Dorbala; Marcelo Di Carli; Guido Germano; Yuka Otaki; Balaji K Tamarappoo; Damini Dey; Daniel S Berman; Piotr J Slomka
Journal:  JACC Cardiovasc Imaging       Date:  2018-03-14

5.  A smartphone-based survey in mHealth to investigate the introduction of the artificial intelligence into cardiology.

Authors:  Daniele Giansanti; Lisa Monoscalco
Journal:  Mhealth       Date:  2021-01-20

6.  Supporting Real World Decision Making in Coronary Diseases Using Machine Learning.

Authors:  Peter Kokol; Jan Jurman; Tajda Bogovič; Tadej Završnik; Jernej Završnik; Helena Blažun Vošner
Journal:  Inquiry       Date:  2021 Jan-Dec       Impact factor: 1.730

7.  Determinants of In-Hospital Mortality After Percutaneous Coronary Intervention: A Machine Learning Approach.

Authors:  Subhi J Al'Aref; Gurpreet Singh; Alexander R van Rosendael; Kranthi K Kolli; Xiaoyue Ma; Gabriel Maliakal; Mohit Pandey; Bejamin C Lee; Jing Wang; Zhuoran Xu; Yiye Zhang; James K Min; S Chiu Wong; Robert M Minutello
Journal:  J Am Heart Assoc       Date:  2019-03-05       Impact factor: 5.501

8.  A Three-Dimensional Deep Convolutional Neural Network for Automatic Segmentation and Diameter Measurement of Type B Aortic Dissection.

Authors:  Yitong Yu; Yang Gao; Jianyong Wei; Fangzhou Liao; Qianjiang Xiao; Jie Zhang; Weihua Yin; Bin Lu
Journal:  Korean J Radiol       Date:  2020-11-03       Impact factor: 3.500

9.  A machine learning approach for the prediction of pulmonary hypertension.

Authors:  Andreas Leha; Kristian Hellenkamp; Bernhard Unsöld; Sitali Mushemi-Blake; Ajay M Shah; Gerd Hasenfuß; Tim Seidler
Journal:  PLoS One       Date:  2019-10-25       Impact factor: 3.240

10.  The Artificial Intelligence in Digital Radiology: Part 2: Towards an Investigation of acceptance and consensus on the Insiders.

Authors:  Francesco Di Basilio; Gianluca Esposisto; Lisa Monoscalco; Daniele Giansanti
Journal:  Healthcare (Basel)       Date:  2022-01-14
  10 in total

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