Machines equipped with deep-learning algorithms may be as good as humans in detecting cancer in ultrasound images and in identifying it in pathology reports, according to recent news out of Samsung, the Regenstrief Institute, and Indiana University. Evidence continues to mount when it comes to the potential of artificial intelligence to help health providers spot signs of illness in patient, including such deadly maladies as cancer. Samsung Medison, for example, has updated its RS80A ultrasound imaging machine with a feature it's calling S-Detect for Breast to analyze breast lesions. It uses big data collected from breast-exam cases and recommends whether a particular lesion is benign or malignant, according to a report in Kurzweil Accelerating Intelligence. The affiliate of Samsung Electronics designed the update for use in lesion segmentation, characteristic analysis, and assessment processes for more accurate results, the company said in a statement.

Medical imaging is expected to be one of the early useful applications of artificial intelligence and machine learning in healthcare. And a slew of deals have been built around that premise in the last year or so--IBM Watson Health bought cloud-based imaging company Merge for 1 billion; Philips partnered with Hitachi to incorporate AI into its image management; and GE added deep learning software from startup Arterys to its cardiac imaging. Now, another major cloud-based imaging startup is working to incorporate machine learning, first into X-ray analysis and eventually into other imaging modalities including CT and MRI. The Goldman Sachs-backed startup Imaging Advantage, which reportedly tapped into up to 250 million in debt in January 2015, has partnered with the Massachusetts Institute of Technology as well as Harvard Medical School and Massachusetts General Hospital to develop an artificial intelligence engine known as Singularity Healthcare. The result is expected to launch this quarter.