Christopher P. Austin, MD - Director, National Center for Advancing Translational Sciences
Two favorite quotes are at the top of my mind this month: “Much is known, but unfortunately in different heads.” and “Be the change you want to see in the world.”
Most often, when people talk about artificial intelligence (AI) they mean a particular kind of AI called machine learning (ML). This is the process of uncovering patterns in data using algorithms and then using those algorithms to make predictions about new data. For example, the recent advances in mammography for the diagnosis of breast cancers, taking a collection of images from CT scans and trying to find the features that discriminate the benign and malignant tumours.
Chris Bickel - Senior Scientific Illustrator at Science
The vision and voice behind the Science design, graphics, photography, and multimedia teams. The views presented do not represent official editorial positions of AAAS.
The image needs to instantly engage the audience while also sparking their curiosity. Above all, it must be accurate.
For this week’s cover I created a story of the SARS-CoV-2 main viral protease, one with impact and movement.
Microsoft is pleased to host “Hack on FHIR", along with health data developers who are gathering at the FHIR Dev Days conference June 15-18, 2020. Get coding time, explore the FHIR spec, and learn the platforms helping organizations innovate using technology that removes barriers to interoperability.
Do machine learning algorithms require a systemic approach to validation and monitoring once they are deployed? Regenstrief CEO Peter Embi, MD, makes the case for creating a surveillance system for algorithms akin to pharmacovigilance.