Spaces:
Sleeping
Sleeping
| import gradio as gr | |
| import joblib | |
| import pandas as pd | |
| import json | |
| # Load the trained model | |
| model = joblib.load("optimized_heart_failure_model.pkl") | |
| # Load feature names used during training | |
| with open("feature_names.json", "r") as f: | |
| feature_names = json.load(f) | |
| # Define the prediction function | |
| def predict_heart_failure(age_category, alcohol_drinkers, chest_scan, covid_positive, physical_health_days, mental_health_days, sleep_hours, bmi): | |
| # Initialize all features to 0 | |
| input_data = {feature: 0 for feature in feature_names} | |
| # Handle Age Category | |
| input_data[f"AgeCategory_{age_category}"] = 1 # Set the selected age category to 1 | |
| # Handle categorical inputs | |
| input_data[f"AlcoholDrinkers_{alcohol_drinkers}"] = 1 # Alcohol Drinkers | |
| input_data[f"ChestScan_{chest_scan}"] = 1 # Chest Scan | |
| input_data[f"CovidPos_{covid_positive}"] = 1 # Covid Positive | |
| # Handle numeric inputs | |
| input_data["PhysicalHealthDays"] = physical_health_days | |
| input_data["MentalHealthDays"] = mental_health_days | |
| input_data["SleepHours"] = sleep_hours | |
| input_data["BMI"] = bmi | |
| # Create a DataFrame with the required feature names | |
| input_df = pd.DataFrame([input_data]) | |
| # Configure pandas to display all columns | |
| pd.set_option('display.max_columns', None) # Display all columns | |
| pd.set_option('display.width', None) # Disable line-wrapping for wide DataFrames | |
| # Ensure all required features are present | |
| for feature in feature_names: | |
| if feature not in input_df.columns: | |
| input_df[feature] = 0 # Fill missing features with default value (e.g., 0) | |
| print("Inputs received in the app:") | |
| print(input_df) | |
| # Ensure no extra features are included | |
| input_df = input_df[feature_names] | |
| # Make a prediction | |
| prediction = model.predict(input_df)[0] | |
| print(f"Prediction: {prediction}") | |
| return "High likelihood of heart failure" if prediction == 1 else "Low likelihood of heart failure" | |
| # Define Gradio inputs | |
| gradio_inputs = [ | |
| gr.Radio( | |
| ["18-24", "25-34", "35-44", "45-54", "55-64", "65-74", "75-79", "80 or older"], | |
| label="Age Category" | |
| ), | |
| gr.Radio(["Yes", "No"], label="Alcohol Drinkers"), | |
| gr.Radio(["Yes", "No"], label="Chest Scan"), | |
| gr.Radio(["Yes", "No"], label="COVID Positive"), | |
| gr.Slider(0, 30, step=1, label="Physical Health Days"), | |
| gr.Slider(0, 30, step=1, label="Mental Health Days"), | |
| gr.Slider(0, 12, step=0.5, label="Sleep Hours"), | |
| gr.Slider(10, 50, step=0.1, label="BMI") | |
| ] | |
| # Set up the Gradio interface | |
| interface = gr.Interface( | |
| fn=predict_heart_failure, | |
| inputs=gradio_inputs, | |
| outputs="text", | |
| title="Heart Failure Risk Prediction", | |
| description="This app predicts the likelihood of heart failure based on health and lifestyle inputs." | |
| ) | |
| # Launch the app | |
| if __name__ == "__main__": | |
| interface.launch() |