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| import gradio as gr | |
| import pandas as pd | |
| import pickle | |
| # Load model RF using pickle | |
| with open('random_forest_model.joblib', 'rb') as f: | |
| best_rf_model = pickle.load(f) | |
| def predict_heart_disease(Age, Sex, ChestPainType, RestingBP, Cholesterol, FastingBS, RestingECG, MaxHR, ExerciseAngina, Oldpeak, ST_Slope): | |
| # Map categorical inputs to numeric values | |
| sex_mapping = {"Female": 0, "Male": 1} | |
| chest_pain_mapping = {"TA": 0, "ATA": 1, "NAP": 2, "ASY": 3} | |
| fasting_bs_mapping = {"< 120 mg/dl": 0, "> 120 mg/dl": 1} | |
| resting_ecg_mapping = {"Normal": 0, "ST": 1, "LVH": 2} | |
| exercise_angina_mapping = {"No": 0, "Yes": 1} | |
| st_slope_mapping = {"Up": 0, "Flat": 1, "Down": 2} | |
| # Adapt input data to model format | |
| input_data = { | |
| 'Age': int(Age), | |
| 'Sex': sex_mapping[Sex], | |
| 'ChestPainType': chest_pain_mapping[ChestPainType], | |
| 'RestingBP': int(RestingBP), | |
| 'Cholesterol': int(Cholesterol), | |
| 'FastingBS': fasting_bs_mapping[FastingBS], | |
| 'RestingECG': resting_ecg_mapping[RestingECG], | |
| 'MaxHR': int(MaxHR), | |
| 'ExerciseAngina': exercise_angina_mapping[ExerciseAngina], | |
| 'Oldpeak': float(Oldpeak), | |
| 'ST_Slope': st_slope_mapping[ST_Slope] | |
| } | |
| # Input data to input dataframe | |
| input_df = pd.DataFrame([input_data]) | |
| # Run prediction | |
| prediction = best_rf_model.predict(input_df) | |
| # Return output with doctor's advice | |
| prediction_message = ( | |
| "Based on your inputs, there is no evidence of heart disease. " | |
| "It's important to maintain a healthy lifestyle and consider regular check-ups." | |
| ) if prediction[0] == 0 else ( | |
| "Based on your inputs, there may be possible evidence of heart disease. " | |
| "Please consult a healthcare professional for a thorough evaluation and further guidance." | |
| ) | |
| # Return both the prediction message and image | |
| return prediction_message, image_url | |
| # Image URL | |
| image_url = "heart.png" | |
| # Set input and outputs of interface | |
| iface = gr.Interface( | |
| fn=predict_heart_disease, | |
| inputs=[ | |
| gr.Number(label="Age", value=40), | |
| gr.Radio(label="Sex", choices=["Female", "Male"], type="value", value="Male"), | |
| gr.Radio(label="Chest Pain Type", choices=["TA", "ATA", "NAP", "ASY"], type="value", value="ATA"), | |
| gr.Number(label="Resting BP (Blood Pressure)", value=140), | |
| gr.Number(label="Cholesterol", value=289), | |
| gr.Radio(label="Fasting BS", choices=["< 120 mg/dl", "> 120 mg/dl"], type="value", value="< 120 mg/dl"), | |
| gr.Radio(label="Resting ECG", choices=["Normal", "ST", "LVH"], type="value", value="ST"), | |
| gr.Number(label="Max HR (Maximum Heart Rate)", value=172), | |
| gr.Radio(label="Exercise Angina", choices=["No", "Yes"], type="value", value="No"), | |
| gr.Number(label="Oldpeak: Numeric value measured in depression", value=0), | |
| gr.Radio(label="ST Slope", choices=["Up", "Flat", "Down"], type="value", value="Down") | |
| ], | |
| outputs=[gr.Text(label="Prediction"), gr.Image(value=image_url, label="Image", show_label=True)], | |
| title="Heart Disease Prediction", | |
| description="Please enter the following details:", | |
| theme=gr.themes.Soft() | |
| ) | |
| # Launch Gradio | |
| iface.launch(debug=True) |