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This course will teach you how to work with health data, using machine learning models to find actionable insights.
Through a step-by-step guided case study, you will learn practical skills that you can apply immediately!
We will use a case study: Opioid Abuse Prediction for a clinic
Topics we will cover:
Health Data (sources, types, features, error handling)
Logistics of machine learning
What predictive model features are, and how to create them
A statistical primer, highlighting key machine learning models and concepts
Build a decision tree, logistic regression and random forest through
Opioid abuse prediction case study
KNIME (a free machine learning software, no coding required!)
Assess model performance
Output presentation and implementation
I have worked in the data rich healthcare space for over 17 years.
I'm passionate about pragmatically utilizing health data to find actionable insights, thereby improving patient care.
I've worked for a variety of health care organizations including insurers, hospitals, pharmaceutical companies and software startups.
I know how to get value out of healthcare data.