[colincsl]

When looking at the performance, it doesn't seem like the LSTM adds very much compared to simpler multi-layer perceptrons. I wonder if that is because temporal information isn't very useful or because the LSTM wasn't capable of learning some of the more complicated temporal patterns.

I would love to play around with the data, unfortunately, I assume it's private (for good reason) due to potentially sensitive patient data.

If anyone is interested in related methods for time series, I just put up code for our recent action segmentation paper using Temporal Convolutional Networks (https://github.com/colincsl/TemporalConvolutionalNetworks). I would be very interested in trying this model on the ICU data. In my experience, TCNs are much better at learning complex temporal pattern than LSTMs.

[jacek]

That's true, according to the paper improvement over MLP is negligible. It looks like the model is very small and that might be a reason for relatively low performance.

[zackchase]

The performance of multilayer perceptrons and linear models is significant. The paper additionally allows the MLP and linear models to "cheat" by giving them heavily hand-engineered features incorporating extensive prior knowledge. Even with this benefit, the LSTM outperforms the baselines, but the improvement is considerably smaller.

[zackchase]

The performance improvement over