As part of our project review, September 30th, Rob Donald presented a report on the results of his research with the Bayesian Neural Network.
For us mere mortals the concept really isn’t easy to understand, but Rob found an excellent way to illustrate how the BANN works. It went something like this:
Take a full set of measures for an individual patient and present them to 100 clinicians. How many of the 100 predict an adverse hypotension event will occur in the next hour?
That’s what the BANN is doing – being 100 clinicians with different opinions.
In Rob’s research the clinicians are already getting it right 35% of the time, but this is only the beginning.
When he’s added the functionality for the prediction engine these clinicians will be getting it right much more often.