AyurVaidya
Multi-system medical treatment recommendation using XGBoost.
Recommends treatments across 10 medical traditions — Allopathic, Ayurveda, TCM, Siddha, Unani, Kampo, Korean TM, African TM, Naturopathic, and Integrative medicine — using a 66-feature clinical profile.
Installation
pip install ayurvaidya
Quick Start
from ayurvaidya import AyurVaidya
# Loads the model from Hugging Face Hub automatically
model = AyurVaidya()
# Predict with a 66-feature vector
result = model.predict(your_features)
print(result) # e.g. "Ayurveda"
# Get probabilities for all 10 systems
probs = model.predict_proba(your_features)
print(probs) # {"African TM": 0.02, "Allopathic": 0.15, "Ayurveda": 0.45, ...}
Performance
| Metric | Score |
|---|---|
| Accuracy | 88.47% |
| Weighted F1 | 0.88 |
| Weighted Precision | 0.89 |
| Weighted Recall | 0.88 |
Links
Important
This is a research tool trained on synthetic data. It is NOT intended for clinical decision-making without proper validation and regulatory approval.
License
MIT
1 maintainer
Metadata
1 maintainer
Release files for ayurvaidya 0.1.0
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