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.

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.

Aiming to develop and market AI algorithms for diagnosing prostate cancer on MRI scans, IBM Watson Health is working with Guerbet, a France-based maker of contrast agents used in medical imaging.

A meta-analysis of 14 studies has shown AI algorithms correctly diagnose diseases in medical imaging around 87% of the time while ruling out specific diseases with 93% accuracy.

Machine learning can read cardiac MRIs with the same accuracy as a physician, with much higher speed, according to a recent study published in Circulation: Cardiovascular Imaging and reported by Cardiovascular Business.