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Cardiology

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Artificial Intelligence-Powered Blockchains for Cardiovascular Medicine.

The Canadian journal of cardiology
Clinical databases, particularly those composed of big data, face growing security challenges. Blockchain, the open, decentralized, distributed public ledger technology powering cryptocurrency, records transactions securely without the need for third...

A Primer on the Present State and Future Prospects for Machine Learning and Artificial Intelligence Applications in Cardiology.

The Canadian journal of cardiology
The artificial intelligence (AI) revolution is well underway, including in the medical field, and has dramatically transformed our lives. An understanding of the basics of AI applications, their development, and challenges to their clinical implement...

The Role of Machine Learning in Cardiovascular Pathology.

The Canadian journal of cardiology
Machine learning has seen slow but steady uptake in diagnostic pathology over the past decade to assess digital whole-slide images. Machine learning tools have incredible potential to standardise, and likely even improve, histopathologic diagnoses, b...

Generative Adversarial Networks in Cardiology.

The Canadian journal of cardiology
Generative adversarial networks (GANs) are state-of-the-art neural network models used to synthesise images and other data. GANs brought a considerable improvement to the quality of synthetic data, quickly becoming the standard for data-generation ta...

Artificial Intelligence in Cardiovascular Imaging: "Unexplainable" Legal and Ethical Challenges?

The Canadian journal of cardiology
Nowhere is the influence of artificial intelligence (AI) likely to be more profoundly felt than in health care, from patient triage and diagnosis to surgery and follow-up. Over the medium-term, these effects will be more acute in the cardiovascular i...

The Evolving Role of Artificial Intelligence in Cardiac Image Analysis.

The Canadian journal of cardiology
Research in artificial intelligence (AI) has progressed over the past decade. The field of cardiac imaging has seen significant developments using newly developed deep learning methods for automated image analysis and AI tools for disease detection a...

Opening the Black Box: The Promise and Limitations of Explainable Machine Learning in Cardiology.

The Canadian journal of cardiology
Many clinicians remain wary of machine learning because of longstanding concerns about "black box" models. "Black box" is shorthand for models that are sufficiently complex that they are not straightforwardly interpretable to humans. Lack of interpre...

Health Technology Assessment for Cardiovascular Digital Health Technologies and Artificial Intelligence: Why Is It Different?

The Canadian journal of cardiology
Innovations in health care are growing exponentially, resulting in improved quality of and access to care, as well as rising societal costs of care and variable reimbursement. In recent years, digital health technologies and artificial intelligence h...

Overview of featurization techniques used in traditional versus emerging deep learning-based algorithms for automated interpretation of the 12-lead ECG.

Journal of electrocardiology
Automated interpretation of the 12-lead ECG has remained an underpinning interest in decades of research that has seen a diversity of computing applications in cardiology. The application of computers in cardiology began in the 1960s with early resea...