How to Bring Analytics and AI into the Clinical Setting
Healthcare organizations are capturing petabytes of digital information across electronic health records, genomic sequences, and IoT data. Using this data to improve clinical practice requires AI technologies that bring disparate data together with state-of-the-art accuracy. However, building actionable insights with analytics and machine learning in a clinical setting is no easy task. In this eBook, we focus on how informatics leaders from the Medical University of South Carolina (MUSC) and UCLA Health are building a strategy for modern cloud analytics. We’ll cover: Common obstacles healthcare organizations face in achieving their strategic goals surrounding big data projects. Best practices for big data from informatics experts Opportunities to transform healthcare with AI and ML.
