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Cardiology

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Machine learning for cardiology.

Minerva cardiology and angiology
This paper reviews recent cardiology literature and reports how artificial intelligence tools (specifically, machine learning techniques) are being used by physicians in the field. Each technique is introduced with enough details to allow the underst...

The Role of Artificial Intelligence and Machine Learning in Clinical Cardiac Electrophysiology.

The Canadian journal of cardiology
In recent years, numerous applications for artificial intelligence (AI) in cardiology have been found, due in part to large digitized data sets and the evolution of high-performance computing. In the discipline of cardiac electrophysiology (EP), a nu...

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

Herzschrittmachertherapie & Elektrophysiologie
Big data and applications of artificial intelligence (AI), such as machine learning or deep learning, will enrich healthcare in the future and become increasingly important. Among other things, they have the potential to avoid unnecessary examination...

The Role of Artificial Intelligence in Echocardiography.

Current cardiology reports
PURPOSE OF REVIEW: Echocardiography is an indispensable tool in diagnostic cardiology and is fundamental to clinical care. Significant advances in cardiovascular imaging technology paralleled by rapid growth in electronic medical records, miniaturize...

Clinical applications of artificial intelligence in cardiology on the verge of the decade.

Cardiology journal
Artificial intelligence (AI) has been hailed as the fourth industrial revolution and its influence on people's lives is increasing. The research on AI applications in medicine is progressing rapidly. This revolution shows promise for more precise dia...

Machine Learning in Cardiology-Ensuring Clinical Impact Lives Up to the Hype.

Journal of cardiovascular pharmacology and therapeutics
Despite substantial advances in the study, treatment, and prevention of cardiovascular disease, numerous challenges relating to optimally screening, diagnosing, and managing patients remain. Simultaneous improvements in computing power, data storage,...

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

Arquivos brasileiros de cardiologia
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...

Automatic diagnosis of the 12-lead ECG using a deep neural network.

Nature communications
The role of automatic electrocardiogram (ECG) analysis in clinical practice is limited by the accuracy of existing models. Deep Neural Networks (DNNs) are models composed of stacked transformations that learn tasks by examples. This technology has re...