EdgeMed Clinical BERT

Fine-tuned BERT model for emergency triage ESI level classification, part of the EdgeMed edge intelligence healthcare routing framework.

Model Details

  • Base model: BERT (clinical fine-tuned)
  • Task: ESI triage classification (ESI-1 to ESI-5)
  • Training data: 1,267 KTAS-ED emergency department patients
  • Accuracy: 71.7%

ESI Levels

Level Severity SLA
ESI-1 Resuscitation < 2 min
ESI-2 Emergent < 10 min
ESI-3 Urgent < 30 min
ESI-4 Less Urgent < 60 min
ESI-5 Non-Urgent < 120 min

Usage

from transformers import AutoTokenizer, AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("Mahdiya/edgemed-clinical-bert") model = AutoModelForSequenceClassification.from_pretrained("Mahdiya/edgemed-clinical-bert")

Citation

EdgeMed: A Lightweight Edge Intelligence Framework for Preference-Aware Emergency Healthcare Routing

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