An electronic sock that detects an unhealthy walking style linked with diabetes and poor circulation shows promise for preventing foot ulcers and amputation. The novel research is set to benefit the many patients with diabetes who have clogged arteries in the legs and is presented for the first time at EHRA 2024 ..read more

Too often, the first sign of cardiovascular disease may be a major event like a heart attack, stroke or cardiac arrest. Now, researchers and clinicians at Mayo Clinic are using artificial intelligence (AI) technology to flag heart problems earlier, boosting the abilities of a diagnostic test that has been around for over a century—the electrocardiogram (ECG ..read more

A driving simulation study has shown we are one step closer to monitoring our heart health in real time via a tiny device worn in the ear ..read more

A technology from the 19th century meets one from the 21st to better help doctors predict who'll survive a heart surgery ..read more

Nearly 200 million people around the globe have coronary heart disease, which accounts for about one in every six deaths, according to the British Heart Foundation. That's why the recent and rapid rise in wearable electronic health-monitoring devices with heart rate-measuring electrocardiograms (ECG) represents a significant step forward. By detecting cardiovascular ailments and helping assess overall cardiac health, wearable ECGs save lives, not to mention exorbitant hospital care costs ..read more

Wearable devices often pick up noisy electrocardiograms (ECGs), which can hinder artificial intelligence (AI)-based detection of cardiovascular disease ..read more

Investigators from Brigham and Women's Hospital and Keio University in Japan have developed a deep learning artificial intelligence model to screen electrocardiogram (ECG) for signs of atrial septal defects (ASD). This condition can cause heart failure and is underreported due to a lack of symptoms before irreversible complications arise. Their results are published in eClinicalMedicine ..read more

A new deep learning application provides an automated screening method for left ventricular (LV) systolic dysfunction. The condition substantially reduces the pumping capacity of the heart and is associated with frequent hospitalizations and a twofold risk of premature death. LV dysfunction is preventable with timely detection and initiation of medications. However, identifying the disease before symptom onset has not been feasible ..read more

Symptom-driven electrocardiogram (ECG) recording plays a significant role in the detection of post-ablation atrial fibrillation recurrence (AFR). However, making timely medical contact whenever symptoms occur may not be practical. The authors of an article published in Cardiovascular Innovations and Applications deployed a deep learning (DL)-based handheld device to facilitate symptom-driven monitoring ..read more

Firefighters regularly risk their lives in dangerous situations, but most deaths on duty are not directly caused by fire or smoke inhalation. Instead, approximately 40% of on-duty fatalities come from sudden cardiac death ..read more