Telemedicine offers emerging opportunities to reduce barriers to obesity care faced by healthcare providers, patients and health plans, according to a paper published online in Obesity, The Obesity Society’s flagship journal.

It has been estimated that by 2030 nearly 80% of adults in the United States will have pre-obesity or obesity.

A major new study in Radiology shows that artificial intelligence (AI) is a promising tool for breast cancer detection in screening mammography programs.

Mammograms acquired through population-based breast cancer screening programs produce a significant workload for radiologists. AI has been proposed as an automated second reader for mammograms that could help reduce this workload.

Researchers at the Yale Cardiovascular Data Science (CarDS) Lab have developed an artificial intelligence (AI)-based model for clinical diagnosis that can use electrocardiogram (ECG) images, regardless of format or layout, to diagnose multiple heart rhythm and conduction disorders.

Hitachi, Ltd. (TSE: 6501, Hitachi), University of Utah Health (U of U Health), and Regenstrief Institute, Inc. (Regenstrief) announced the development of an AI method to improve care for patients with type 2 diabetes mellitus who need complex treatment. One in 10 adults worldwide have been diagnosed with type 2 diabetes,

Myocarditis (inflammation of the heart muscle) is usually caused by viruses, e.g. in COVID-19 disease. However, it can also be induced by medication, toxic substances or in the context of a rheumatological disease. Clinical assessment is difficult due to widely varying symptoms, from fatigue to chest pain, palpitations, shortness of breath, and, rarely, sudden cardiac death, the latter associated with sports activity.

Heart transplantation can be a lifesaving operation for patients with end-stage heart failure. However, many patients experience organ transplant rejection, in which the immune system begins attacking the transplanted organ. But detecting transplant rejection is challenging - in its early stages, patients may not experience symptoms, and experts do not always agree on the degree and severity of the rejection.

An artificial intelligence (AI) tool can accurately and consistently classify breast density on mammograms, according to a study in Radiology: Artificial Intelligence.

Breast density reflects the amount of fibroglandular tissue in the breast commonly seen on mammograms. High breast density is an independent breast cancer risk factor, and its masking effect of underlying lesions reduces the sensitivity of mammography.