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disease-classifier
ARUNAGIRINATHAN/disease-classifier
disease-classifier is a text classification model from ARUNAGIRINATHAN. Use it when you need a label for a piece of text. The card lists the license as mit.
A multi-class disease classification model built with XGBoost that predicts diseases based on patient symptoms, age, and gender.
Access
Public
Updated Dec 20, 2025
Repo size
15.2 MB
Likes
3
Public
Repo makeup
Click a slice to open those files.
.joblib15.2 MB · 89%
At a glance
- Task
- Text Classification
- License
- mit
- Access
- Public
- Created
- Dec 14, 2025
- Updated
- Dec 20, 2025
- SHA
- 50e4c1a1
Try a prompt
Datasets
Model card
From the Hugging Face model README
Disease Classifier (XGBoost)
A multi-class disease classification model built with XGBoost that predicts diseases based on patient symptoms, age, and gender.
Model Overview
| Property | Value |
|---|---|
| Algorithm |  |
| Objective |  |
| Task |  |
| Input |  |
| Output |  |
🚀 Quick Start
Installation
pip install huggingface_hub joblib pandas numpy xgboost scikit-learn
Load and Use the Model
import joblib
import pandas as pd
import numpy as np
from huggingface_hub import hf_hub_download
# Download model from Hugging Face
REPO_ID = "ARUNAGIRINATHAN/disease-classifier"
model = joblib.load(hf_hub_download(REPO_ID, "xgboost_model.joblib"))
label_encoder = joblib.load(hf_hub_download(REPO_ID, "label_encoder.joblib"))
feature_columns = joblib.load(hf_hub_download(REPO_ID, "feature_columns.joblib"))
Made with ❤️ for healthcare AI research
- Task
- Text Classification
- License
- mit
- Languages
- en
- Created
- Dec 14, 2025
- Updated
- Dec 20, 2025