Nothing beats XB for a rapid check on an algorithm, at least for me, so when I started a research project on pediatric croup, my TI was super useful.
Quick background: 75% of admissions for pediatric croup are unnecessary in the US, a huge waste of healthcare dollars and an unnecessary burden on the child and family. I started a research project about a year ago trying to come up with a risk calculator that could predict with reasonable accuracy whether any particular croup patients required admission. Data collection was completed a couple of months ago but extensive statistical analysis has failed to produce strong associations between patient characteristics and need for admission, possibly hindered by the fact that only 117 patients in my hospital pool met research inclusion criteria. So I decided to test out a neural network to see if I could tease out hidden associations beyond the realm of statistics.
Who said the TI was obsolete?
For the curious, here's the neural net program in its current state: