Spaces:
Sleeping
Sleeping
| import streamlit as st | |
| import joblib | |
| import pandas as pd | |
| # Load trained model | |
| model = joblib.load("diabetes_model.joblib") | |
| # Streamlit UI | |
| st.title("Diabetes Prediction App") | |
| st.write("Enter patient data to predict diabetes") | |
| # Input fields | |
| pregnancies = st.number_input("Pregnancies", min_value=0, max_value=20) | |
| glucose = st.number_input("Glucose Level", min_value=0, max_value=200) | |
| blood_pressure = st.number_input("Blood Pressure", min_value=0, max_value=200) | |
| skin_thickness = st.number_input("Skin Thickness", min_value=0, max_value=100) | |
| insulin = st.number_input("Insulin Level", min_value=0, max_value=900) | |
| bmi = st.number_input("BMI", min_value=0.0, max_value=60.0) | |
| dpf = st.number_input("Diabetes Pedigree Function", min_value=0.0, max_value=3.0) | |
| age = st.number_input("Age", min_value=0, max_value=120) | |
| # Prediction | |
| if st.button("Predict"): | |
| features = [[pregnancies, glucose, blood_pressure, skin_thickness, insulin, bmi, dpf, age]] | |
| prediction = model.predict(features)[0] | |
| result = "Diabetic" if prediction == 1 else "Not Diabetic" | |
| st.write(f"Prediction: **{result}**") | |