Table 5.
Top-k ∘ | Upper Bound ⋆ | Patient representation learning methods | ||||||
---|---|---|---|---|---|---|---|---|
RNN-DAE | RNN-AE | SDAs | PCA | k-means | GMM | Hand | ||
k=1 | 0.962 | 0.604 | 0.617 | 0.212 | 0.449 | 0.181 | 0.607 | 0.605 |
k=2 | 0.878 | 0.534 | 0.514 | 0.195 | 0.384 | 0.208 | 0.503 | 0.503 |
k=3 | 0.769 | 0.452 | 0.419 | 0.177 | 0.305 | 0.144 | 0.416 | 0.417 |
∘“Top-k” represents the average accuracy of all the patients, where accuracy for one patient is the average number of correct results included in its top k predicted comorbiditie(s). The top-k comorbiditie(s) is/are sorted by predicted probabilities, with k=1,2,3.
⋆“Upper Bound” shows the best results achievable (i.e., all the correct comorbidities assigned to all the patients)