A novel screening approach developed by physicians at the Lewis Katz School of Medicine at Temple University shows significant promise for improving the detection of pulmonary arterial hypertension (PAH)—a life-threatening form of heart failure related to high blood pressure in the lung circulation that is often overlooked due to vague symptoms such as fatigue and shortness of breath.

The new research, published online April 5 in the American Heart Journal, shows that the virtual echocardiography screening tool (VEST), when incorporated into the electronic medical record (EMR) system, can generate accurate PAH risk scores—without the need for time-consuming manual calculations. The approach is the first of its kind in the field of pulmonary vascular medicine.

Researchers have developed a cost-effective, AI-powered system for diagnosing nystagmus—a condition causing involuntary eye movements—using smartphone videos and cloud-based analysis. Unlike traditional methods like VNG, which are expensive and cumbersome, this deep learning model uses real-time facial landmark tracking to assess eye movement metrics remotely. A pilot study with 20 participants showed its accuracy closely matched traditional devices, highlighting its potential for telehealth use and broader clinical application.

One-pot recipes make preparing meals quick and easy. And one-pot 3D-printing could do the same for additive manufacturing. Now, researchers publishing in ACS Central Science have demonstrated a new resin that simultaneously creates solid objects and dissolvable structural supports, depending on what type of light the resin is exposed to. The approach could increase the applications for 3D-printed objects, including tissue engineering scaffolds, joints and hinges.