Tabular Classification
Scikit-learn
Joblib
ONNX
English
healthcare
medical
disease-prediction
ensemble
scikit-learn
Eval Results (legacy)
Instructions to use Av1447/Health with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use Av1447/Health with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("Av1447/Health", "sklearn_model.joblib") ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - Notebooks
- Google Colab
- Kaggle
File size: 643 Bytes
6ed3a47 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 | {
"Asthma": [
"Salbutamol Inhaler",
"Montelukast Tablet"
],
"Pneumonia": [
"Amoxicillin",
"Paracetamol"
],
"Tuberculosis": [
"Isoniazid",
"Rifampicin",
"Pyrazinamide",
"Ethambutol"
],
"Hypertension": [
"Amlodipine",
"Losartan"
],
"Migraine": [
"Paracetamol",
"Sumatriptan"
],
"Flu": [
"Oseltamivir",
"Paracetamol"
],
"Diabetes": [
"Metformin",
"Glimepiride"
],
"Cold": [
"Paracetamol",
"Cetirizine"
],
"Malaria": [
"Chloroquine",
"Artemether-Lumefantrine"
],
"COVID-19": [
"Paracetamol",
"Vitamin C",
"Zinc"
]
} |