There have been significant advancements in endovascular technology over the past decade. Increasingly complex disease processes are being addressed in a less invasive fashion, while still relying on standard 2-dimensional greyscale fluoroscopy imagi...
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...
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...
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 (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...
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...
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...