With massive amounts of data flowing from EMRs, wearables, and countless other new sources, the potential for machine learning and AI to transform healthcare is perhaps more drastic and profound than any other industry. However, there are unique obstacles that exist in healthcare that can make it difficult to apply machine learning. Oftentimes, data are missing, inaccurate or stored in silos. Connecting patient records across providers and insurers is a challenge due to the lack of interoperability and reliable patient identification methods. And in some cases, such as when dealing with patients with rare conditions, data is insufficient or incomplete.
In this course, you'll gain practical knowledge that will enable you to overcome these hurdles and apply the latest advances in healthcare AI tools and techniques to:
Connect health data from disparate sources (e.g. EHRs, mobile, wearables)
Identify patterns and determine the most effective treatments
Predict and improve patient and financial outcomes
Model disease progression
Enable personalized care and precision medicine