Datapalooza Panelists Address Implications of Artificial Intelligence Healthcare Informatics Magazine Health IT

One of the more interesting panels at last week's Health Datapalooza featured four speakers involved in the application of artificial intelligence to healthcare, including the creation of predictive models. In areas involving massive amounts of information in the diagnostic and genomic space, machine learning is already in use today, and the FDA is starting to approve applications of deep learning. For instance, a company called Arterys recently won FDA approval for its Cardio DL application, which uses deep learning to automate time-consuming analyses and tasks that are performed manually by clinicians today. Although they each come at it from a different angle based on their company's focus, there were several overarching themes the Datapalooza panelists tackled about the application of algorithms in healthcare, including the importance of transparency to getting clinician engagement. Getting buy-in from clinicians is a huge challenge, said Eric Just, a senior vice president for product development at Health Catalyst, which builds analytics and decision support tools for its health system customers.