Literature DB >> 33478654

Machine Learning and the Future of Cardiovascular Care: JACC State-of-the-Art Review.

Giorgio Quer1, Ramy Arnaout2, Michael Henne3, Rima Arnaout4.   

Abstract

The role of physicians has always been to synthesize the data available to them to identify diagnostic patterns that guide treatment and follow response. Today, increasingly sophisticated machine learning algorithms may grow to support clinical experts in some of these tasks. Machine learning has the potential to benefit patients and cardiologists, but only if clinicians take an active role in bringing these new algorithms into practice. The aim of this review is to introduce clinicians who are not data science experts to key concepts in machine learning that will allow them to better understand the field and evaluate new literature and developments. The current published data in machine learning for cardiovascular disease is then summarized, using both a bibliometric survey, with code publicly available to enable similar analysis for any research topic of interest, and select case studies. Finally, several ways that clinicians can and must be involved in this emerging field are presented.
Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  artificial intelligence; bibliometric analysis; cardiology; deep learning; literature search; machine learning

Mesh:

Year:  2021        PMID: 33478654      PMCID: PMC7839163          DOI: 10.1016/j.jacc.2020.11.030

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


  74 in total

Review 1.  The Future of Cardiovascular Computed Tomography: Advanced Analytics and Clinical Insights.

Authors:  Edward D Nicol; Bjarne L Norgaard; Philipp Blanke; Amir Ahmadi; Jonathon Weir-McCall; Pal Maurovich Horvat; Kelly Han; Jeroen J Bax; Jonathon Leipsic
Journal:  JACC Cardiovasc Imaging       Date:  2019-06

2.  Building medical image classifiers with very limited data using segmentation networks.

Authors:  Ken C L Wong; Tanveer Syeda-Mahmood; Mehdi Moradi
Journal:  Med Image Anal       Date:  2018-08-04       Impact factor: 8.545

3.  Validation of deep-learning image reconstruction for coronary computed tomography angiography: Impact on noise, image quality and diagnostic accuracy.

Authors:  Dominik C Benz; Georgios Benetos; Georgios Rampidis; Elia von Felten; Adam Bakula; Aleksandra Sustar; Ken Kudura; Michael Messerli; Tobias A Fuchs; Catherine Gebhard; Aju P Pazhenkottil; Philipp A Kaufmann; Ronny R Buechel
Journal:  J Cardiovasc Comput Tomogr       Date:  2020-01-13

4.  Machine learning of clinical variables and coronary artery calcium scoring for the prediction of obstructive coronary artery disease on coronary computed tomography angiography: analysis from the CONFIRM registry.

Authors:  Subhi J Al'Aref; Gabriel Maliakal; Gurpreet Singh; Alexander R van Rosendael; Xiaoyue Ma; Zhuoran Xu; Omar Al Hussein Alawamlh; Benjamin Lee; Mohit Pandey; Stephan Achenbach; Mouaz H Al-Mallah; Daniele Andreini; Jeroen J Bax; Daniel S Berman; Matthew J Budoff; Filippo Cademartiri; Tracy Q Callister; Hyuk-Jae Chang; Kavitha Chinnaiyan; Benjamin J W Chow; Ricardo C Cury; Augustin DeLago; Gudrun Feuchtner; Martin Hadamitzky; Joerg Hausleiter; Philipp A Kaufmann; Yong-Jin Kim; Jonathon A Leipsic; Erica Maffei; Hugo Marques; Pedro de Araújo Gonçalves; Gianluca Pontone; Gilbert L Raff; Ronen Rubinshtein; Todd C Villines; Heidi Gransar; Yao Lu; Erica C Jones; Jessica M Peña; Fay Y Lin; James K Min; Leslee J Shaw
Journal:  Eur Heart J       Date:  2020-01-14       Impact factor: 29.983

Review 5.  State-of-the-Art Deep Learning in Cardiovascular Image Analysis.

Authors:  Geert Litjens; Francesco Ciompi; Jelmer M Wolterink; Bob D de Vos; Tim Leiner; Jonas Teuwen; Ivana Išgum
Journal:  JACC Cardiovasc Imaging       Date:  2019-08

Review 6.  Proposed Requirements for Cardiovascular Imaging-Related Machine Learning Evaluation (PRIME): A Checklist: Reviewed by the American College of Cardiology Healthcare Innovation Council.

Authors:  Partho P Sengupta; Sirish Shrestha; Béatrice Berthon; Emmanuel Messas; Erwan Donal; Geoffrey H Tison; James K Min; Jan D'hooge; Jens-Uwe Voigt; Joel Dudley; Johan W Verjans; Khader Shameer; Kipp Johnson; Lasse Lovstakken; Mahdi Tabassian; Marco Piccirilli; Mathieu Pernot; Naveena Yanamala; Nicolas Duchateau; Nobuyuki Kagiyama; Olivier Bernard; Piotr Slomka; Rahul Deo; Rima Arnaout
Journal:  JACC Cardiovasc Imaging       Date:  2020-09

7.  Predicting individual physiologically acceptable states at discharge from a pediatric intensive care unit.

Authors:  Cameron S Carlin; Long V Ho; David R Ledbetter; Melissa D Aczon; Randall C Wetzel
Journal:  J Am Med Inform Assoc       Date:  2018-12-01       Impact factor: 4.497

8.  Using neural attention networks to detect adverse medical events from electronic health records.

Authors:  Jiebin Chu; Wei Dong; Kunlun He; Huilong Duan; Zhengxing Huang
Journal:  J Biomed Inform       Date:  2018-10-15       Impact factor: 6.317

9.  Fall Risk Classification in Community-Dwelling Older Adults Using a Smart Wrist-Worn Device and the Resident Assessment Instrument-Home Care: Prospective Observational Study.

Authors:  Yang Yang; John P Hirdes; Joel A Dubin; Joon Lee
Journal:  JMIR Aging       Date:  2019-06-07

10.  Adverse Drug Reaction Detection in Social Media by Deepm Learning Methods.

Authors:  Zahra Rezaei; Hossein Ebrahimpour-Komleh; Behnaz Eslami; Ramyar Chavoshinejad; Mehdi Totonchi
Journal:  Cell J       Date:  2019-12-15       Impact factor: 2.479

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  36 in total

Review 1.  Evaluating Medical Therapy for Calcific Aortic Stenosis: JACC State-of-the-Art Review.

Authors:  Brian R Lindman; Devraj Sukul; Marc R Dweck; Mahesh V Madhavan; Benoit J Arsenault; Megan Coylewright; W David Merryman; David E Newby; John Lewis; Frank E Harrell; Michael J Mack; Martin B Leon; Catherine M Otto; Philippe Pibarot
Journal:  J Am Coll Cardiol       Date:  2021-12-07       Impact factor: 24.094

Review 2.  Extra-coronary Calcification and Cardiovascular Events: What Do We Know and Where Are We Heading?

Authors:  Dixitha Anugula; Rhanderson Cardoso; Gowtham R Grandhi; Ron Blankstein; Khurram Nasir; Mouaz Al-Mallah; Dipan J Shah; Miguel Cainzos-Achirica
Journal:  Curr Atheroscler Rep       Date:  2022-08-30       Impact factor: 5.967

3.  Using deep learning-based natural language processing to identify reasons for statin nonuse in patients with atherosclerotic cardiovascular disease.

Authors:  Ashish Sarraju; Jean Coquet; Alban Zammit; Antonia Chan; Summer Ngo; Tina Hernandez-Boussard; Fatima Rodriguez
Journal:  Commun Med (Lond)       Date:  2022-07-15

4.  Artificial intelligence opportunities in cardio-oncology: Overview with spotlight on electrocardiography.

Authors:  Daniel Sierra-Lara Martinez; Peter A Noseworthy; Oguz Akbilgic; Joerg Herrmann; Kathryn J Ruddy; Abdulaziz Hamid; Ragasnehith Maddula; Ashima Singh; Robert Davis; Fatma Gunturkun; John L Jefferies; Sherry-Ann Brown
Journal:  Am Heart J Plus       Date:  2022-04-01

Review 5.  Artificial Intelligence in Cardiovascular Medicine: Current Insights and Future Prospects.

Authors:  Ikram U Haq; Karanjot Chhatwal; Krishna Sanaka; Bo Xu
Journal:  Vasc Health Risk Manag       Date:  2022-07-12

Review 6.  Cardiovascular Disease Screening in Women: Leveraging Artificial Intelligence and Digital Tools.

Authors:  Demilade A Adedinsewo; Amy W Pollak; Sabrina D Phillips; Taryn L Smith; Anna Svatikova; Sharonne N Hayes; Sharon L Mulvagh; Colleen Norris; Veronique L Roger; Peter A Noseworthy; Xiaoxi Yao; Rickey E Carter
Journal:  Circ Res       Date:  2022-02-17       Impact factor: 23.213

7.  Machine Learning-Based Prediction of Myocardial Recovery in Patients With Left Ventricular Assist Device Support.

Authors:  Veli K Topkara; Pierre Elias; Rashmi Jain; Gabriel Sayer; Daniel Burkhoff; Nir Uriel
Journal:  Circ Heart Fail       Date:  2021-12-24       Impact factor: 8.790

8.  Can Machine Learning Help Simplify the Measurement of Diastolic Function in Echocardiography?

Authors:  Rima Arnaout
Journal:  JACC Cardiovasc Imaging       Date:  2021-07-14

9.  A Comprehensive Explanation Framework for Biomedical Time Series Classification.

Authors:  Praharsh Ivaturi; Matteo Gadaleta; Amitabh C Pandey; Michael Pazzani; Steven R Steinhubl; Giorgio Quer
Journal:  IEEE J Biomed Health Inform       Date:  2021-07-27       Impact factor: 7.021

10.  Mitral Valve Atlas for Artificial Intelligence Predictions of MitraClip Intervention Outcomes.

Authors:  Yaghoub Dabiri; Jiang Yao; Vaikom S Mahadevan; Daniel Gruber; Rima Arnaout; Wolfgang Gentzsch; Julius M Guccione; Ghassan S Kassab
Journal:  Front Cardiovasc Med       Date:  2021-12-10
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