Susan is a Global Product Marketing Manager for AI at SAS. She has her Ph.D. in Human Factors and Ergonomics, having used analytics to quantify and compare mental models of how humans learn complex operations. Throughout her well-rounded career, she has held roles in user centered design, product management, customer insights, consulting and operational risk. Susan recently completed her Master of Science in Analytics, focusing on healthcare analytics. She also holds a patent for a software navigation system to guide users through dynamically changing systems.
The application of IoT devices and artificial intelligence in healthcare presents numerous opportunities in use cases like training, research, end-of-life care, treatment, keeping well, early detection, diagnosis, and decision-making.
Generative adversarial networks (GANs) are one of the newer machine learning algorithms that data scientists are tapping into. When I first heard it, I wondered how can networks be adversarial? I envisioned networks with swords drawn going at it. Close… but I can assure you that no networks were harmed in the making of this article.
Decision trees are one of the top machine learning algorithms used by data scientists. Decision trees use supervised learning to classify problems. Even if you are not a data scientist, chances are you can interpret the visual output from a decision tree.
