Treatment options for rheumatoid arthritis have often relied on trial and error. Now Mayo Clinic researchers are exploring the use of artificial intelligence (AI) and pharmacogenomics to predict how patients will respond to treatments, and to personalize care. Findings were published in Arthritis Care & Research.

Membrane-associated proteins play a vital role in a variety of cellular processes, yet little is known about the membrane-association mechanism. Lipoprotein-associated phospholipase A2 (Lp-PLA2) is one such protein with an important role in cardiovascular health, but its mechanism of action on the phospholipid membrane was unknown.

A computer analysis of hundreds of thousands of secure email messages between doctors and patients found that most doctors use language that is too complex for their patients to understand. The study also uncovered strategies some doctors use to overcome communication barriers.

Pulmonary embolisms are dangerous, lung-clogging blot clots. In a pilot study, scientists at the Icahn School of Medicine at Mount Sinai showed for the first time that artificial intelligence (AI) algorithms can detect signs of these clots in electrocardiograms (EKGs), a finding which may one day help doctors with screening.

The COVID-19 pandemic has had a major impact on mental health across the globe. Depression is predicted to be the leading cause of lost life years due to illness by 2030. At the same time, less than 1 in 5 people receive appropriate treatment.

Digital interventions - which package up psychotherapeutic components into a computer program or mobile app - have been proposed as a way of meeting the unmet demand for psychological treatment.

Emergency room and urgent care clinics are typically busy and patients often have to wait many hours before they can be seen, evaluated and receive treatment. Waiting for x-rays to be interpreted by radiologists can contribute to this long wait time because radiologists often read x-rays for a large number of patients.

For nearly 50 years, scientists have struggled to solve one of nature’s most perplexing challenges - predicting the complex 3D shape a string of amino acids will fold into as it becomes a working protein. This year, scientists have shown that artificial intelligence (AI)-driven software can achieve this long-standing goal and predict accurate protein structures by the thousands. To honor this feat, Science has named AI-powered protein prediction as its 2021 breakthrough of the year.