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. 

Developments in vastly scalable IT infrastructure will soon increase the rate at which machine learning systems gain the capacity to transform the field of medical imaging across clinical, operational and business domains. Moreover, if the pace seems to be picking up, that’s because data management on a massive scale has advanced exponentially over just the past several years. 

A new project is seeking to make MRI scans up to 10 times faster by capturing less data. NYU’s Center for Advanced Imaging Innovation and Research (CAI2R) is working with the Facebook Artificial Intelligence Research group to “train artificial neural networks to recognize the underlying structure of the images to fill in views omitted from the accelerated scan.”

Machine learning is one of the hottest topics in radiology and all of healthcare, but reading the latest and greatest ML research can be difficult, even for experienced medical professionals. A new analysis written by a team at Northern Ireland’s Belfast City Hospital and published in the American Journal of Roentgenology was written with that very problem in mind.

A compilation of the latest news in AI and machine learning