Machine learning (ML) efforts have focused predominantly on clinical applications rather than operations. We will explore two practical uses to demonstrate how machine learning can help augment healthcare operations. The first example describes how Amsterdam University Medical Center is using computer vision to monitor the progression of tumors in the liver. CT scans are a very workload-intensive process for the radiologists. Using computer vision, they can measure more than just the largest two tumors, enabling them to render a more complete diagnosis. The process is also faster and more cost effective. The second use case is about how to use natural language processing to manage and derive insights from large medical corpuses. One customer saved over 5,000 person hours per month using SAS software to extract key concepts from over 30,000 documents.