Literature DB >> 28545640

Artificial Intelligence in Precision Cardiovascular Medicine.

Chayakrit Krittanawong1, HongJu Zhang2, Zhen Wang3, Mehmet Aydar4, Takeshi Kitai5.   

Abstract

Artificial intelligence (AI) is a field of computer science that aims to mimic human thought processes, learning capacity, and knowledge storage. AI techniques have been applied in cardiovascular medicine to explore novel genotypes and phenotypes in existing diseases, improve the quality of patient care, enable cost-effectiveness, and reduce readmission and mortality rates. Over the past decade, several machine-learning techniques have been used for cardiovascular disease diagnosis and prediction. Each problem requires some degree of understanding of the problem, in terms of cardiovascular medicine and statistics, to apply the optimal machine-learning algorithm. In the near future, AI will result in a paradigm shift toward precision cardiovascular medicine. The potential of AI in cardiovascular medicine is tremendous; however, ignorance of the challenges may overshadow its potential clinical impact. This paper gives a glimpse of AI's application in cardiovascular clinical care and discusses its potential role in facilitating precision cardiovascular medicine.
Copyright © 2017 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  big data; cognitive computing; deep learning; machine learning

Mesh:

Year:  2017        PMID: 28545640     DOI: 10.1016/j.jacc.2017.03.571

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


  153 in total

Review 1.  New Concepts in Sudden Cardiac Arrest to Address an Intractable Epidemic: JACC State-of-the-Art Review.

Authors:  Sanjiv M Narayan; Paul J Wang; James P Daubert
Journal:  J Am Coll Cardiol       Date:  2019-01-08       Impact factor: 24.094

2.  Deep learning for cardiovascular medicine: a practical primer.

Authors:  Chayakrit Krittanawong; Kipp W Johnson; Robert S Rosenson; Zhen Wang; Mehmet Aydar; Usman Baber; James K Min; W H Wilson Tang; Jonathan L Halperin; Sanjiv M Narayan
Journal:  Eur Heart J       Date:  2019-07-01       Impact factor: 29.983

3.  Why imaging data alone is not enough: AI-based integration of imaging, omics, and clinical data.

Authors:  Andreas Holzinger; Benjamin Haibe-Kains; Igor Jurisica
Journal:  Eur J Nucl Med Mol Imaging       Date:  2019-06-15       Impact factor: 9.236

Review 4.  Artificial Intelligence Transforms the Future of Health Care.

Authors:  Nariman Noorbakhsh-Sabet; Ramin Zand; Yanfei Zhang; Vida Abedi
Journal:  Am J Med       Date:  2019-01-31       Impact factor: 4.965

5.  Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation.

Authors:  Edward G Jones; Andrew P Landstrom
Journal:  J Vis Exp       Date:  2019-01-16       Impact factor: 1.355

Review 6.  [Artificial intelligence in cardiology : Relevance, current applications, and future developments].

Authors:  Bettina Zippel-Schultz; Carsten Schultz; Dirk Müller-Wieland; Andrew B Remppis; Martin Stockburger; Christian Perings; Thomas M Helms
Journal:  Herzschrittmacherther Elektrophysiol       Date:  2021-01-15

Review 7.  Artificial intelligence in personalized cardiovascular medicine and cardiovascular imaging.

Authors:  Ikram-Ul Haq; Iqraa Haq; Bo Xu
Journal:  Cardiovasc Diagn Ther       Date:  2021-06

8.  Paving a Better Path for Patients Dying of Heart Disease.

Authors:  Haider J Warraich; Robert J Mentz; Adrian F Hernandez
Journal:  Circulation       Date:  2018-03-20       Impact factor: 29.690

Review 9.  Current Management and Future Directions of Heart Failure With Preserved Ejection Fraction: a Contemporary Review.

Authors:  Chayakrit Krittanawong; Marrick L Kukin
Journal:  Curr Treat Options Cardiovasc Med       Date:  2018-03-20

10.  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
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