• Project Title: Analyzing Sleep Data With Machine Learning

  • BASIS Advisor: Mr. Hansen

  • Internship Location: Somnoware Healthcare Systems

  • Onsite Mentor: Mr. Mathew Mammen

My internship will experiment with machine learning and healthcare. I will be working for a company named Somnoware that enables chronic obstructive pulmonary disease and sleep apnea care providers to reduce cost and improve patient outcomes. I will be studying machine learning and taking sleep data to do a predictive analysis and predict what diseases a person is prone to based on that data. I aim to find which machine learning method is most effective in accurately predicting obstructive sleep apnea and will learn about probabilistic graphical models, pattern recognition, and numerical computing. Then, I will gain familiarity with Octave and MATlab, collect data from classmates using Fitbits, and train the test data. I will decide which modeling is most accurate, test the model, and debug any efficiency problems. I expect that neural networks will be the most efficient because they can have many layers with non-linearities and are effective at modelling highly complex non-linear relationships. I hope to discover how machine learning can transform the way that we sleep and the accuracy of analyses made by doctors in regards to sleeping disorders. The sleep data that I collect from my classmates can be useful in showing other teenagers how you can plan sleep in order to minimize disease risk.