EHR prediction on SICdb
0.765AUROCReMed
Evaluation results
| Method | Links | |
|---|---|---|
| ReMedTrain mode=Multi, Tokenization Strategy=LLM Align2026.03 | 0.765 | |
| ReMedTrain mode=Multi, Tokenization Strategy=EnTok2026.03 | 0.763 | |
| GenHPFTrain mode=Multi, Tokenization Strategy=LLM Align2026.03 | 0.761 | |
| ReMedTrain mode=Multi, Tokenization Strategy=MLTok2026.03 | 0.758 | |
| ReMedTrain mode=Single, Tokenization Strategy=EnTok2026.03 | 0.757 | |
| YAIB*Train mode=Single, Tokenization Strategy=Code-base2026.03 | 0.756 | |
| ReMedTrain mode=Single, Tokenization Strategy=LLM Align2026.03 | 0.756 | |
| ReMedTrain mode=Single, Tokenization Strategy=MLTok2026.03 | 0.753 | |
| GenHPFTrain mode=Multi, Tokenization Strategy=EnTok2026.03 | 0.748 | |
| GenHPFTrain mode=Multi, Tokenization Strategy=MLTok2026.03 | 0.748 | |
| Rajikomar*Train mode=Single, Tokenization Strategy=Code-base2026.03 | 0.747 | |
| GenHPFTrain mode=Single, Tokenization Strategy=LLM Align2026.03 | 0.747 | |
| YAIB*Train mode=Multi, Tokenization Strategy=Code-base2026.03 | 0.746 | |
| GenHPFTrain mode=Single, Tokenization Strategy=EnTok2026.03 | 0.745 | |
| GenHPFTrain mode=Single, Tokenization Strategy=MLTok2026.03 | 0.741 | |
| Rajikomar*Train mode=Multi, Tokenization Strategy=Code-base2026.03 | 0.737 |