Artificial intelligence (AI) is an integral part of clinical decision support systems (CDSS), offering methods to approximate human reasoning and computationally infer decisions. Such methods are generally based on medical knowledge, either directly encoded with rules or automatically extracted from medical data using machine learning (ML). ML techniques, such as Artificial Neural Networks (ANNs) and support vector machines (SVMs), are based on mathematical models with parameters that can be optimally tuned using appropriate algorithms. The ever-increasing computational capacity of today’s computer systems enables more complex ML systems with millions of parameters, bringing AI closer to human intelligence. With this objective, the term deep learning (DL) has been introduced to characterize ML based on deep ANN (DNN) architectures with multiple layers of artificial neurons. Despite all of these promises, the impact of AI in current clinical practice is still limited. However, this could change shortly, as the significantly increased papers in AI, machine learning and deep learning in cardiology show. We highlight the significant achievements of recent years in nearly all areas of cardiology and underscore the mounting evidence suggesting how AI will take a central stage in the field.

ChatGPT (Generative Pre-trained Transformer) is a large-scale language processing model, with possibilities for professional patient support in a patient-friendly way. The aim of the study was to examine the accuracy and reproducibility of ChatGPT in answering questions about knowledge and management of heart failure (HF). First, we recorded 47 most frequently asked questions by patients about HF. The answers of ChatGPT to these questions were independently assessed by two researchers. ChatGPT was able to render the definition of the disease in a very simple and explanatory way. It listed a number of the most important causes of HF and the most important risk factors for its occurrence. It provided correct answers about the most important diagnostic tests and why they are recommended. In addition, it answered health and dietary questions, such as the daily fluid and the alcohol intake. ChatGPT listed the most important classes of drugs in HF and their mechanism of action. It also answered with arguments to questions about patient’s sex life, whether they could work, drive, or travel by plane. The performance of ChatGPT was described as very good as it was able to adequately answer all questions posed to it.

Introduction Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease, which is estimated to affect 20–30% of the adult population in Europe. Several studies have shown an association of NAFLD with multiple cardiovascular risk factors such as abdominal obesity,...

Robots are defined as programmable machines that can perform specified tasks. Medical robots are emerging solutions in the field of cardiology leveraging recent technological innovations of control systems, sensors, actuators, and imaging modalities. Robotic platforms are successfully applied for percutaneous coronary intervention, invasive cardiac electrophysiology procedures as well as surgical operations including minimally invasive aortic and mitral valve repair, coronary artery bypass procedures, and structural heart diseases. Furthermore, machines are used as staff-assisting tools to support nurses with repetitive clinical duties i.e., food delivery. High precision and resolution allow for excellent maneuverability, enabling the performance of medical procedures in challenging anatomies that are difficult or impossible using conventional approaches. Moreover, robot-assisted techniques protect operators from occupational hazards, reducing exposure to ionizing radiation, and limiting risk of orthopedic injuries. Novel automatic systems provide advantages for patients, ensuring device stability with optimized utilization of fluoroscopy. The acceptance of robotic technology among healthcare providers as well as patients paves the way for widespread clinical application in the field of cardiovascular medicine. However, incorporation of robotic systems is associated with some disadvantages including high costs of installation and expensive disposable instrumentations, the need for large operating room space, and the necessity of dedicated training for operators due to the challenging learning curve of robotic-assisted interventional systems.