Decoding Brain Signals: How Azure Machine Learning Contributes to Neuroscience and Biomedical Research

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Description

Patients who have injuries or tumors on the neuron connectivity have difficulties in connecting the visual stimulus and cognition. The cutting edge research done by professor from Stanford University discovered that by decoding the ECoG signal collected from the brain, the machine learning algorithm can discover what image is actually displayed to the patients, which bridges the gap between visual stimulus and cognition.

In this talk, we will discuss: general introduction of the ML algorithm in decoding ECoG signal; show the benchmark with the original paper; the challenges and main differences in converting Matlab code to R code; how we build the end-to-end analytics pipeline using Cortana Intelligence Suites and how we build the starter experiment to launch March Madness competition

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