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UMCU/
DutchCADRADS_fromRadioReports_Masked

Name: DutchCADRADS_fromRadioReports_Masked
Availability: InStock

UMCU/CardioDeBERTa.nl_clinical

finetune

gpl-3.0

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We identified the CADRADS scores in 1429 radiology reports using regular expressions for the CADRADS directly and for the degrees of stenosis. For the training we masked the direct CADRADS patterns.

Model card:

Field	Value
Task	Multi-class sequence/text classification
Number of samples	1,429
Number of classes	6
Labels	`0, 1, 2, 3, 4, 5`
Base model	`UMCU/CardioBERTa.nl_clinical`
Architecture	`RobertaForSequenceClassification`
Classification head	Newly initialized before fine-tuning
Validation strategy	Stratified 10-fold cross-validation
Trained fold	Fold 0 only
Fold 0 train size	1,286
Fold 0 validation size	143
Class weighting	Yes

Label distribution:

Label	Count	Percentage
0	345	24.1%
1	281	19.7%
2	333	23.3%
3	317	22.2%
4	135	9.4%
5	18	1.3%

Class weights:

Label	Weight
0	0.6914
1	0.8505
2	0.7168
3	0.7494
4	1.7568
5	12.6078

10-fold CV results.

json

"average_results": {
    "avg_eval_accuracy": 0.863542795232936,
    "std_eval_accuracy": 0.03399941533079611,
    "avg_eval_f1": 0.8609888740211058,
    "std_eval_f1": 0.034077598782922706,
    "avg_eval_precision": 0.8642976260040041,
    "std_eval_precision": 0.03264535733017625,
    "avg_eval_recall": 0.863542795232936,
    "std_eval_recall": 0.03399941533079611
  }

UMCU/DutchCADRADS_fromRadioReports_Masked

UMCU/
DutchCADRADS_fromRadioReports_Masked