Literature DB >> 32491009

Artificial Intelligence in Cardiology: Concepts, Tools and Challenges - "The Horse is the One Who Runs, You Must Be the Jockey".

Erito Marques de Souza Filho1,2, Fernando de Amorim Fernandes1, Celine Lacerda de Abreu Soares1, Flavio Luiz Seixas1, Alair Augusto Sarmet M D Dos Santos1, Ronaldo Altenburg Gismondi1, Evandro Tinoco Mesquita1, Claudio Tinoco Mesquita1.   

Abstract

The recent advances at hardware level and the increasing requirement of personalization of care associated with the urgent needs of value creation for the patients has helped Artificial Intelligence (AI) to promote a significant paradigm shift in the most diverse areas of medical knowledge, particularly in Cardiology, for its ability to support decision-making and improve diagnostic and prognostic performance. In this context, the present work does a non-systematic review of the main papers published on AI in Cardiology, focusing on its main applications, potential impacts and challenges.

Entities:  

Year:  2020        PMID： 32491009     DOI： 10.36660/abc.20180431

Source DB:  PubMed          Journal:  Arq Bras Cardiol        ISSN： 0066-782X            Impact factor:   2.000


  9 in total

1.  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

2.  Artificial Algorithms Outperform Traditional Models in Predicting Coronary Artery Disease.

Authors:  Lutfu Askin; Okan Tanrıverdi; Mustafa Cetin
Journal:  Arq Bras Cardiol       Date:  2021-12       Impact factor: 2.667

Review 3.  Artificial Intelligence in Modern Medicine - The Evolving Necessity of the Present and Role in Transforming the Future of Medical Care.

Authors:  Pradnya Brijmohan Bhattad; Vinay Jain
Journal:  Cureus       Date:  2020-05-09

4.  What Can COVID-19 Teach Us about Using AI in Pandemics?

Authors:  Krzysztof Laudanski; Gregory Shea; Matthew DiMeglio; Mariana Rastrepo; Cassie Solomon
Journal:  Healthcare (Basel)       Date:  2020-12-01

5.  Machine Learning Algorithms to Distinguish Myocardial Perfusion SPECT Polar Maps.

Authors:  Erito Marques de Souza Filho; Fernando de Amorim Fernandes; Christiane Wiefels; Lucas Nunes Dalbonio de Carvalho; Tadeu Francisco Dos Santos; Alair Augusto Sarmet M D Dos Santos; Evandro Tinoco Mesquita; Flávio Luiz Seixas; Benjamin J W Chow; Claudio Tinoco Mesquita; Ronaldo Altenburg Gismondi
Journal:  Front Cardiovasc Med       Date:  2021-11-11

Review 6.  Artificial intelligence in the diagnosis and management of arrhythmias.

Authors:  Venkat D Nagarajan; Su-Lin Lee; Jan-Lukas Robertus; Christoph A Nienaber; Natalia A Trayanova; Sabine Ernst
Journal:  Eur Heart J       Date:  2021-10-07       Impact factor: 29.983

7.  Machine learning-based predictive modeling of depression in hypertensive populations.

Authors:  Chiyoung Lee; Heewon Kim
Journal:  PLoS One       Date:  2022-07-29       Impact factor: 3.752

8.  Initial application of deep learning to borescope detection of endoscope working channel damage and residue.

Authors:  Monique T Barakat; Mohit Girotra; Subhas Banerjee
Journal:  Endosc Int Open       Date:  2022-01-14

9.  Ethics, Artificial Intelligence and Cardiology.

Authors:  Erito Marques de Souza Filho; Fernando de Amorim Fernandes; Nikolas Cunha de Assis Pereira; Claudio Tinoco Mesquita; Ronaldo Altenburg Gismondi
Journal:  Arq Bras Cardiol       Date:  2020-09       Impact factor: 2.667
  9 in total

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