Machine learning can help electrophysiologists or other heart specialists decide whether a patient is a good candidate for a pacemaker or implantable cardioverter defibrillator, according to a study published Oct. 3 in PLOS One.

Machine learning can be combined with virtual or augmented reality to train surgery residents in sensitive spinal procedures.

Software that uses AI to make cardiac-ultrasound experts of healthcare workers with no prior ultrasound experience has received “Breakthrough Device” designation from the FDA.

Worldwide, research is booming around AI applications for predicting and treating cancer with ever more precise and personalized approaches. However, a new literature review has found a shortfall of AI-inclusive studies looking at cancer outcomes and survivorship.

If a newly tested AI system for reading chest X-rays achieves widespread adoption, patients presenting in the ER with symptoms of pneumonia can expect an up or down diagnosis—and with it the start of a treatment plan—in 10 seconds.

A wrist-worn step tracker is an adequate tool to measure exercise capacity and the health status of patients, replacing a standardized six-minute walking test in a clinical setting, according to new research from Intermountain Healthcare.

Researchers in Germany have developed an AI-based method for identifying pediatric acute appendicitis using biomarkers like blood and protein readings obtained in routine lab tests.

Several major charitable organizations are banding together to prevent 6 million deaths in 10 countries by 2030 using Big Data to provide precision medicine.