Leaders of HR departments are looking to AI for help improving the employee experience. As part of the effort, some 59% are considering or already adding virtual employee assistants like chatbots.

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.

If the researchers behind a new report on AI in healthcare are right, the technology could cut nonclinical workers’ workload by 40% while also slashing clinical tasks by 33%.

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.

Engineers and roboticists in Europe have invented an artificial skin that can provide wearers with haptic feedback—replicating the human sense of touch—for potential applications in various fields, including medical rehabilitation and physical therapy. 

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.

Contrary to popular perceptions, while much leading-edge innovation involving AI is coming out of China, the advances emanating from the Middle Kingdom are limited to just a few platform technologies and market segments.

Kheiron Medical Technologies, a London-based machine learning startup focused on helping radiologists detect cancer at an early stage, has raised $22 million in a Series A funding round.

Deep-learning analysis of eye scans has proven superior to conventional analysis of the same images for the task of detecting and tracking vision diseases like glaucoma and age-related macular degeneration.