Table 5 Performance of predicting medical codes of the next visit
From: EHR phenotyping via jointly embedding medical concepts and words into a unified vector space
Model | Top-20 recall | Top-30 recall | Top-40 recall |
|---|---|---|---|
Concatenation-One | 0.489 ±0.004 | 0.590 ±0.004 | 0.661 ±0.004 |
SVD | 0.478 ±0.004 | 0.588 ±0.004 | 0.652 ±0.004 |
LDA | 0.431 ±0.004 | 0.530 ±0.004 | 0.605 ±0.004 |
Codes-JointSG | 0.499 ±0.003 | 0.592 ±0.003 | 0.662 ±0.003 |
Words-JointSG | 0.437 ±0.004 | 0.536 ±0.004 | 0.609 ±0.004 |
Concatenation-JointSG | 0.506 ±0.003 | 0.599 ±0.003 | 0.670 ±0.003 |