Machine learning algorithms can now identify lymphedema—a chronic side effect of breast cancer treatment—with 94 percent accuracy, New York University researchers reported this month in mHealth.

Radiology professionals working on artificial intelligence (AI) technologies can learn a lot from studying self-driving vehicles, according to a new commentary published in the Journal of the American College of Radiology.

Convolutional neural networks (CNN) were more accurate than even the most expert dermatologists in detecting skin cancer, researchers reported in Annals of Oncology this week.

Machine learning techniques perform well when tasked with predicting malignancy in breast lesions identified during breast cone-beam CT (CBCT) exams, according to a new study from German researchers published by the American Journal of Roentgenology. One technique, back propagation neural networks (BPN), outperformed two radiologists.

British Prime Minister Theresa May announced this week she will pledge millions of pounds to the fight against cancer through the development of artificial intelligence (AI), Forbes has reported.

A new partnership between University College London Hospitals and the Alan Turing Institute aims to start using artificial intelligence (AI) to perform certain tasks typically carried out by doctors and nurses.

Radiologists, clinical oncologists and industry stakeholders gathered May 16 in London to discuss artificial intelligence (AI) in medical imaging and cancer treatment. The all-day event was organized by the Royal College of Radiologists (RCR) with help from the Alan Turing Institute, Health Data Research UK and the Engineering and Physical Sciences Research Council.

South Korea’s Ministry of Food and Drug Safety announced this week that, for the very first time, it has approved a medical device that uses artificial intelligence (AI) technology.