Introduction

0:02 hello and welcome to this presentation about an online course on data science for ai in healthcare in this talk we are going to give an overview of the course and its development our work is supported by delta grant from the office of the provost at johns hopkins university we also want to acknowledge our colleagues at the center for learning design for their effort in producing and disseminating this course at the malone center for engineering and healthcare we are a collective of scientists with clinical technical and statistical backgrounds with all the news on ai in healthcare recently we realized that we have an interesting perspective to demystify ai in healthcare not only for clinicians but also for engineers this is because when it comes to health care developing in a developing ai method is really about solving a clinical question so it takes not only technical development of the solution but also validating it statistical methods and evaluating its usability in the clinic so we saw an opportunity to translate the technical statistical and clinical dimensions of ai in

1:09 healthcare to make it possible for a broad audience to understand the essential nuances of research in this domain and to critically think about ai and what it would take to build healthcare applications based on the eye the teaching team is shown on the slide here uh it includes me uh mathias and barath anand malphani brian caffo and greg hager all of us affiliated with the malone center at johns hopkins so to kick off this introduction ai and healthcare has actually been around for several decades although it's getting a lot of headlines these days starting in the 1960s health data became digital and this made it possible to imagine a number of ways that computing