Literature DB >> 32370835

Artificial Intelligence in Cardiology: Present and Future.

Francisco Lopez-Jimenez1, Zachi Attia2, Adelaide M Arruda-Olson2, Rickey Carter3, Panithaya Chareonthaitawee2, Hayan Jouni2, Suraj Kapa2, Amir Lerman2, Christina Luong2, Jose R Medina-Inojosa2, Peter A Noseworthy4, Patricia A Pellikka2, Margaret M Redfield2, Veronique L Roger4, Gurpreet S Sandhu2, Conor Senecal2, Paul A Friedman2.   

Abstract

Artificial intelligence (AI) is a nontechnical, popular term that refers to machine learning of various types but most often to deep neural networks. Cardiology is at the forefront of AI in medicine. For this review, we searched PubMed and MEDLINE databases with no date restriction using search terms related to AI and cardiology. Articles were selected for inclusion on the basis of relevance. We highlight the major achievements in recent years in nearly all areas of cardiology and underscore the mounting evidence suggesting how AI will take center stage in the field. Artificial intelligence requires a close collaboration among computer scientists, clinical investigators, clinicians, and other users in order to identify the most relevant problems to be solved. Best practices in the generation and implementation of AI include the selection of ideal data sources, taking into account common challenges during the interpretation, validation, and generalizability of findings, and addressing safety and ethical concerns before final implementation. The future of AI in cardiology and in medicine in general is bright as the collaboration between investigators and clinicians continues to excel.
Copyright © 2020 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.

Year:  2020        PMID: 32370835     DOI: 10.1016/j.mayocp.2020.01.038

Source DB:  PubMed          Journal:  Mayo Clin Proc        ISSN: 0025-6196            Impact factor:   7.616


  21 in total

Review 1.  Utilizing Artificial Intelligence to Enhance Health Equity Among Patients with Heart Failure.

Authors:  Amber E Johnson; LaPrincess C Brewer; Melvin R Echols; Sula Mazimba; Rashmee U Shah; Khadijah Breathett
Journal:  Heart Fail Clin       Date:  2022-03-04       Impact factor: 3.179

Review 2.  Artificial Intelligence Applications in Health Care Practice: Scoping Review.

Authors:  Malvika Sharma; Carl Savage; Monika Nair; Ingrid Larsson; Petra Svedberg; Jens M Nygren
Journal:  J Med Internet Res       Date:  2022-10-05       Impact factor: 7.076

3.  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 4.  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

5.  Noninvasive Vocal Biomarker is Associated With Severe Acute Respiratory Syndrome Coronavirus 2 Infection.

Authors:  Elad Maor; Nir Tsur; Galia Barkai; Ido Meister; Shmuel Makmel; Eli Friedman; Daniel Aronovich; Dana Mevorach; Amir Lerman; Eyal Zimlichman; Gideon Bachar
Journal:  Mayo Clin Proc Innov Qual Outcomes       Date:  2021-05-14

Review 6.  Artificial intelligence-enhanced electrocardiography in cardiovascular disease management.

Authors:  Konstantinos C Siontis; Peter A Noseworthy; Zachi I Attia; Paul A Friedman
Journal:  Nat Rev Cardiol       Date:  2021-02-01       Impact factor: 32.419

Review 7.  Cardiac Phase Space Analysis: Assessing Coronary Artery Disease Utilizing Artificial Intelligence.

Authors:  Mark G Rabbat; Shyam Ramchandani; William E Sanders
Journal:  Biomed Res Int       Date:  2021-04-09       Impact factor: 3.411

8.  Reporting of screening and diagnostic AI rarely acknowledges ethical, legal, and social implications: a mass media frame analysis.

Authors:  Emma K Frost; Stacy M Carter
Journal:  BMC Med Inform Decis Mak       Date:  2020-12-10       Impact factor: 2.796

9.  Digital health innovation in cardiology.

Authors:  Adetola O Ladejobi; Jessica Cruz; Zachi I Attia; Martin van Zyl; Jason Tri; Francisco Lopez-Jimenez; Peter A Noseworthy; Paul A Friedman; Suraj Kapa; Samuel J Asirvatham
Journal:  Cardiovasc Digit Health J       Date:  2020-08-28

10.  Machine Learning Prediction of Biomarkers from SNPs and of Disease Risk from Biomarkers in the UK Biobank.

Authors:  Erik Widen; Timothy G Raben; Louis Lello; Stephen D H Hsu
Journal:  Genes (Basel)       Date:  2021-06-29       Impact factor: 4.141

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