IBM Watson Health has announced a new 10-year, $50 million investment in joint research collaboration projects with Brigham and Women’s Hospital in Boston and Vanderbilt University Medical Center (VUMC) to advance the application of artificial intelligence (AI) in public health.

Zebra Medical Vision announced it has received grants from the Israel Innovation Authority to implement its AI algorithms in three of Israel's largest medical institutions.

The new platform, affectionately called ‘Herman,' analyzes complex patterns in images of pathogen and human cell interactions, and can do so in a fraction of the time normally required.

Kai-Fu Lee, the CEO of a Chinese venture capital firm and former president of Google China, discussed AI and its impact on various sectors of the economy in a new interview with Fox Business.

Testing a previously developed deep-learning algorithm for assessing children’s bone age on x-rays, Harvard researchers have found their tool combined with a radiologist beats three competitors—AI alone, a radiologist alone and a pooled group of unaided experts.

It’s all about the data. We’ve been saying this for years. We can choose to look at this in one of two ways. It’s either a constant truism or it actually evolves and gains mass over time. In the age of artificial intelligence, it is both. 

As an integrated health-delivery network comprising 13 hospital campuses, two research centers and a health plan with more than half a million subscribers sitting atop the biggest biobank with whole exome (DNA) sequence data in existence, Pennsylvania’s Geisinger Health System is one of the best-positioned institutions in the U.S. to explore the possibilities and initial successes of AI in healthcare. The institution is bringing complex algorithmic concepts to everyday patient care and showing others the path forward.

Artificial and augmented intelligence are driving the future of medical imaging. Tectonic is the only way to describe the trend. And medical imaging is at the right place at the right time. Imaging stands to get better, stronger, faster and more efficient thanks to artificial intelligence, including machine learning, deep learning, convolutional neural networks and natural language processing. So why is medical imaging ripe for AI? Check out the opportunities and hear what experts have to say—and see what you should be doing now if you haven’t already started.