Figure 1.

This diagram shows how we have applied RNNs to solve the problem of forecasting of next visits’ time and the codes assigned during each visit. The first layer simply embeds the high-dimensional input vectors in a lower dimensional space. The next layers are the recurrent units (here two layers), which learn the status of the patient at each timestamp as a real-valued vector. Given the status vector, we use two dense layers to generate the codes observed in the next timestamp and the duration until next visit.