KEPTlongfomer is a medical knowledge enhanced version of Longformer that was further pre-trained using contrastive learning. The model achieves SOTA performance on auto ICD coding on MIMIC-III as of 11/12/2022. A sister model for better performance is available here.
Pre-training
We initialized this model from clinical longformer.
And then pretrained with Hierarchical Self-Alignment Pretrain (HSAP) using Knowledge Graph UMLS. This includes (a) Hierarchy, (b) Synonym, (c) Abbreviation. For more info, see section 3.3 in paper. The learning rate was 5e-5, weight decay was 0.01, adam epsilon was 1e-5.
Usage
See our github for how to use this with prompts on auto ICD coding.
With the following result:
| Metric | Score |
|---|---|
| rec_micro | =0.5729403619819988 |
| rec_macro | =0.11342156911120573 |
| rec_at_8 | =0.4094837705486378 |
| rec_at_75 | =0.8470734920535119 |
| rec_at_50 | =0.8005338782352 |
| rec_at_5 | =0.2891628170355805 |
| rec_at_15 | =0.5768778119750537 |
| prec_micro | =0.6411968713105065 |
| prec_macro | =0.12227610414493029 |
| prec_at_8 | =0.7760972716488731 |
| prec_at_75 | =0.197504942665085 |
| prec_at_50 | =0.2768090154211151 |
| prec_at_5 | =0.8483392645314354 |
| prec_at_15 | =0.6178529062870699 |
| f1_micro | =0.6051499904242899 |
| f1_macro | =0.11768251595637802 |
| f1_at_8 | =0.536107150495997 |
| f1_at_75 | =0.32032290907137506 |
| f1_at_50 | =0.411373195944102 |
| f1_at_5 | =0.43131028155283435 |
| f1_at_15 | =0.5966627077602488 |
| auc_micro | =0.9651754312635265 |
| auc_macro | =0.8566590059725866 |
| acc_micro | =0.43384592341105344 |
| acc_macro | =0.08639139221100567 |
- Downloads last month
- 217
This model does not have enough activity to be deployed to Inference API (serverless) yet.
Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.