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README.md
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### 🧠 Key Methodology: Age-Aware Triage
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Our validation revealed that **parsing Age and Gender** from the patient description is critical for accurate risk stratification (e.g., separating "Chest Pain" in a 72M vs 20M). The model effectively learned these demographic risk factors, improving accuracy from 16% to 60%.
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See our [W&B Report](https://wandb.ai/mrlincs-nursing-citizen-development/
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## 🩺 Clinical Framework: Manchester Triage System
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### 🧠 Key Methodology: Age-Aware Triage
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Our validation revealed that **parsing Age and Gender** from the patient description is critical for accurate risk stratification (e.g., separating "Chest Pain" in a 72M vs 20M). The model effectively learned these demographic risk factors, improving accuracy from 16% to 60%.
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See our [W&B Report]([https://api.wandb.ai/links/mrlincs-nursing-citizen-development/yg3hzy60]) for detailed training curves.
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## 🩺 Clinical Framework: Manchester Triage System
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