Welcome to predictive modeling and transforming clinical practice. My name is Laura Wiley, and I am delighted to be your instructor for this course. I'm an Assistant Professor of biomedical informatics and personalized medicine at the University of Colorado, Anschutz Medical Campus. Predictive modeling and transforming clinical practice is the fifth course in the clinical data science specialization. A series of six courses that provides practical, hands-on training, and using electronic medical record data. The first week of this course will introduce you to the basics of clinical prediction modeling, examples of clinical prediction models, and then provide you with an overview of the clinical data science predictive modeling process. In Week 2, you will learn about how to identify which problems are best solved with predictive models and how to work with the people and processes to ensure model acceptability and usability. Week 3, we'll teach you the tools available for implementing predictive models within electronic health records, which you will then use to better understand the implementability and sustainability of your predictive models. Then in Week 4, you will get your hands dirty, actually, building a predictive model using a real clinical dataset and our online computational platform hosted by our industry partner, Google Cloud. Finally, in Week 5, you'll be given a clinical prediction modeling task where you'll be asked to deploy the techniques you've learned. At the end of these five weeks, you will have the knowledge and skills to create prediction models that are acceptable and usable in the clinic. Let's get started learning one of the most in-demand skills for clinical data science.
