An algorithm is only as valuable as its adoption. Speed to value, repeatability, and low-cost solutions can dramatically reduce software and services budgets and free up valuable dollars for other activities. Open-source tools such as Shiny (R) and Flask (Python) have enabled the creation and deployment of data science-based web applications convenient and manageable. In the healthcare data science world, we routinely wrap sophisticated statistical code into such web-based point-and-click solutions. In this talk, you will learn about real-life examples of how one can rapidly operationalize intricate algorithms using web app frameworks.
