Fig. 1. Experimental design for performance comparison of recurrent neural network (RNN) against physicians.

The electronic health record (EHR) data was split into a training and a test set. The training set was used for the development of the RNN (orange path). For each patient (Pat) in the test set, a quasi-random ‘prediction point’ in the time-series was chosen (for more information about quasi-randomness see ‘Methods’). EHR data up to this prediction point was given to physicians and RNN (the rest of the time series data, here denoted as X, was hidden). Both physicians and RNN, had to make a prediction for postoperative AKI at this prediction point.