RadNet and Google Health join forces to use AI for lung cancer screening

Specifically, Google Health will provide scientific expertise and their existing model, while Aidence will use deep learning methods to further develop the existing model in an effort to quickly and accurately predict malignancy of CT-detected lung nodules in a clinical setting. "We are enthusiastic about working on a powerful deep learning model for lung nodule malignancy prediction based on the work of the Aidence and Google teams, as well as making sure that all the other requirements that contribute to the successful deployment of AI in clinical practice are in place, like clinical validation, certification and integration into the clinical workflow," said Aidence cofounder Mark-Jan Harte. Osarogiagbon stressed the potential of a commercially available solution to help identify cancerous cases: "The world looks forward to the rapid development and validation of software that will enhance our ability to find the many lung cancer needles in the giant haystack that is CT-detected lung nodules in today's clinical practice," he said.