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Cardiology

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[Artificial intelligence in cardiology].

Giornale italiano di cardiologia (2006)
Artificial intelligence (AI) in cardiology represents a great opportunity, if further developed in a trustworthy way, to support human intelligence in daily practice. AI could help cardiologists to operate with greater efficacy and efficiency, suppor...

Recent Updates and Technological Developments in Evaluating Cardiac Syncope in the Emergency Department.

Current cardiology reviews
Syncope is a commonly encountered problem in the emergency department (ED), accounting for approximately 3% of presenting complaints. Clinical assessment of syncope can be challenging due to the diverse range of conditions that can precipitate the sy...

Technical and practical aspects of artificial intelligence in cardiology.

Bratislavske lekarske listy
Artificial intelligence (AI) is here to stay. It is not a future anymore, and there are many particular problems in cardiology that are already being solved via machine learning (ML), and many more are to come. AI cannot solve complex tasks yet, and ...

The Emergence of Artificial Intelligence in Cardiology: Current and Future Applications.

Current cardiology reviews
Artificial intelligence technology is emerging as a promising entity in cardiovascular medicine, potentially improving diagnosis and patient care. In this article, we review the literature on artificial intelligence and its utility in cardiology. We ...

Deep learning and the electrocardiogram: review of the current state-of-the-art.

Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
In the recent decade, deep learning, a subset of artificial intelligence and machine learning, has been used to identify patterns in big healthcare datasets for disease phenotyping, event predictions, and complex decision making. Public datasets for ...

Meeting the unmet needs of clinicians from AI systems showcased for cardiology with deep-learning-based ECG analysis.

Proceedings of the National Academy of Sciences of the United States of America
Despite their great promise, artificial intelligence (AI) systems have yet to become ubiquitous in the daily practice of medicine largely due to several crucial unmet needs of healthcare practitioners. These include lack of explanations in clinically...

[Progress in cardiac imaging: from echocardiography to multimodality imaging].

Giornale italiano di cardiologia (2006)
In the last few decades, echocardiography has represented one of the technological fields with the fastest evolution and progress. As a non-invasive method at relative low cost, it is also suitable for the future to an increasingly integrated use in ...

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

Journal of the American College of Cardiology
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 exper...

Artificial Neural Networks in Cardiovascular Diseases and its Potential for Clinical Application in Molecular Imaging.

Current radiopharmaceuticals
In medical imaging, Artificial Intelligence is described as the ability of a system to properly interpret and learn from external data, acquiring knowledge to achieve specific goals and tasks through flexible adaptation. The number of possible applic...