The heart must go on: The spectrum of cardiological diseases ranges from arrhythmias to valve defects to heart attacks. However, the diagnostic means and the forms of therapy with intervention, surgery and medication are just as diverse. Read more about this affair of the heart here.
Systematic screening and support for mental health conditions such as depression, anxiety, or PTSD should become normalised in cardiovascular care, cardiologists urge in a new Consensus Statement.
Traditionally, measuring heart rate requires some sort of wearable device. Now, new research shows how the signal from a household WiFi device can be used for this crucial health monitoring.
Researchers have developed a machine learning algorithm that uses cardiac MRI images to help identify breast cancer patients who may be at risk of cardiotoxicity during cancer treatment. The research, led by cardiologist Dr Paaladinesh Thavendiranathan from Toronto General Hospital University Health Network, was presented at the European Society of Cardiology's Cardio-Oncology Conference in…
New AI-powered solutions for cardiac ultrasound: Italian medical imaging specialist Esaote will be present at the European Society of Cardiology (ESC) Congress 2025, which starts today (29th August) in Madrid.
An unexpected trigger for heart attack: Researchers show that dormant bacteria can contribute to atherosclerotic plaques and fatal myocardial infarction, effectively making it an infectious disease.
An artificial heart valve made from SEBS, a new type of highly durable and biocompatible plastic, could be a step closer to use in humans, following a successful long-term safety test in animals.
An association between specific electrical patterns and structural characteristics of heart scars after a heart attack could offer a new approach for more targeted and effective arrhythmia treatments.
A new AI tool has been shown to accurately predict who would go on to develop leaks in the heart valves – conditions known as regurgitant valvular heart diseases, at a very early stage from an ECG.
A neural network AI has been trained to detect cardiac amyloidosis from a single echocardiogram video of the heart's apical four-chamber view and differentiate it from similar heart conditions.
Analyzing heart imaging and a full spectrum of medical records, a new AI tool can reveal previously hidden information about a patient’s heart health, including predictions of sudden cardiac arrest.
An AI-assisted model can take low-quality MRI heart scans and turn them into high quality images, while reducing the time needed to scan the heart by about 90%.
MRI study of 802 patients shows carotid plaques become more complex over six years, with calcified plaques twice as likely to develop dangerous internal bleeding.
Machine learning (ML) for personalised care, large language models for empathy training of cardiologists, wearable sensor data for better screening, and more: Digital technologies hold great potential to improve diagnosis and treatment of patients with atrial fibrillation (AF). At the ESC 2024 cardiology congress in London, four experts explored the benefits of new solutions and pointed out…
Maternal contractions during childbirth put considerable stress on a baby's heart. Using a new ultrasound technique, researchers were able to predict complications necessitating C-section.
Creating cardiac ‘digital twins’ at a large scale, researchers hope to gather new insights into heart health. This includes effects of age, sex, and lifestyle factors on heart disease risk.
A new 4D flow MRI method could accelerate diagnosis of aortic stenosis, a progressive and potentially fatal heart condition.
Molecular testing provides a more convenient, personalized way of monitoring of heart transplant recipients, according to insights shared at the Annual Meeting and Scientific Sessions of the ISHLT.
Researchers have developed an AI tool that creates synthetic yet medically accurate models of fibrotic heart tissue (heart scarring), aiding treatment planning for atrial fibrillation (AF) patients.
A network of artificial neurons imitating the human brain could help identify patients at risk of a serious arrhythmia from an ECG and avoid many cases of sudden cardiac death, a new study suggests.
