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| import pickle | |
| import pandas as pd | |
| import shap | |
| from shap.plots._force_matplotlib import draw_additive_plot | |
| import gradio as gr | |
| import numpy as np | |
| import matplotlib.pyplot as plt | |
| # load the model from disk | |
| loaded_model = pickle.load(open("heart_xgb.pkl", 'rb')) | |
| # Setup SHAP | |
| explainer = shap.Explainer(loaded_model) # PLEASE DO NOT CHANGE THIS. | |
| # Create the main function for server | |
| def main_func(age, sex, cp, trtbps, chol, fbs, restecg, thalachh,exng,oldpeak,slp,caa,thall): | |
| new_row = pd.DataFrame.from_dict({'age':age,'sex':sex, | |
| 'cp':cp,'trtbps':trtbps,'chol':chol, | |
| 'fbs':fbs, 'restecg':restecg,'thalachh':thalachh,'exng':exng, | |
| 'oldpeak':oldpeak,'slp':slp,'caa':caa,'thall':thall}, | |
| orient = 'index').transpose() | |
| prob = loaded_model.predict_proba(new_row) | |
| shap_values = explainer(new_row) | |
| # plot = shap.force_plot(shap_values[0], matplotlib=True, figsize=(30,30), show=False) | |
| # plot = shap.plots.waterfall(shap_values[0], max_display=6, show=False) | |
| plot = shap.plots.bar(shap_values[0], max_display=8, order=shap.Explanation.abs, show_data='auto', show=False) | |
| plt.tight_layout() | |
| local_plot = plt.gcf() | |
| plt.close() | |
| return {"Low Chance": float(prob[0][0]), "High Chance": 1-float(prob[0][0])}, local_plot | |
| # Create the UI | |
| title = "**Heart Attack Predictor & Interpreter** 🪐" | |
| description1 = """This app takes info from subjects and predicts their heart attack likelihood. Do not use these results for an actual medical diagnosis.""" | |
| description2 = """ | |
| To use the app, simply adjust the inputs and click the "Analyze" button. You can also click one of the examples below to see how it's done! | |
| """ | |
| with gr.Blocks(title=title) as demo: | |
| with gr.Row(): | |
| with gr.Column(): | |
| gr.Markdown(f"# {title}") | |
| gr.Markdown(f"## How does it work?") | |
| gr.Markdown(description1) | |
| gr.Markdown("""---""") | |
| gr.Markdown(description2) | |
| with gr.Column(): | |
| gr.Image("dr.jpg") | |
| gr.Markdown("""---""") | |
| with gr.Row(): | |
| with gr.Column(): | |
| gr.Markdown(f"## Edit the Inputs Below:") | |
| gr.Markdown("""---""") | |
| with gr.Row(): | |
| age = gr.Number(label="Age", info="How old are you?", value=40) | |
| # sex = gr.Radio(["Male", "Female"], label = "What Gender are you?", type = "index") | |
| sex = gr.Radio(["Male", "Female"], label="Sex", info="What gender are you?", type="index") | |
| # sex = gr.Radio(choices=["Male", "Female"]) | |
| cp = gr.Radio(["Typical Angina", "Atypical Angina", "Non-anginal Pain", "Asymptomatic"], label="Chest Pain", info="What kind of chest pain do you have?", type="index") | |
| # cp = gr.Slider(label="Chest Pain Type", minimum=1, maximum=5, value=4, step=1) | |
| # trtbps = gr.Slider(label="Resting blood pressure (in mm Hg)", minimum=1, maximum=200, value=4, step=1) | |
| trtbps = gr.Number(label="trtbps", value=100) | |
| chol = gr.Number(label="chol", value=70) | |
| fbs = gr.Radio(["False", "True"], label="fbs", info="Is your fasting blood sugar > 120 mg/dl?" , type="index") | |
| # restecg = gr.Slider(label="Resting ECG Score", minimum=1, maximum=5, value=4, step=1) | |
| restecg = gr.Dropdown(["Normal", "Having ST-T wave abnormality", "Showing probable or definite left ventricular hypertrophy by Estes' criteria"], label="rest_ecg", type="index") | |
| thalachh = gr.Slider(label="thalach Score", minimum=1, maximum=205, value=4, step=1) | |
| exng = gr.Radio(["No", "Yes"], label="Exercise Induced Angina", type="index") | |
| oldpeak = gr.Slider(label="Oldpeak Score", minimum=1, maximum=10, value=4, step=1) | |
| slp = gr.Slider(label="Slp Score", minimum=1, maximum=5, value=4, step=1) | |
| caa = gr.Slider(label="Number of Major Vessels", minimum=1, maximum=3, value=3, step=1) | |
| thall = gr.Slider(label="Thall Score", minimum=1, maximum=5, value=4, step=1) | |
| with gr.Column(): | |
| gr.Markdown(f"## Output:") | |
| gr.Markdown("""---""") | |
| with gr.Column(visible=True) as output_col: | |
| label = gr.Label(label = "Predicted Label") | |
| local_plot = gr.Plot(label = 'Shap:') | |
| gr.Markdown(f"## Examples:") | |
| gr.Markdown("""---""") | |
| gr.Markdown("### Click on any of the examples below to see how it works:") | |
| gr.Examples([[24,"Male","Typical Angina",4,5,"True","Normal",4,"No",5,1,2,3], [24,"Female","Asymptomatic",4,5,"False","Normal",2,"Yes",1,1,2,3]], [age, sex, cp, trtbps, chol, fbs, restecg, thalachh,exng,oldpeak,slp,caa,thall], [label,local_plot], main_func, cache_examples=True) | |
| submit_btn = gr.Button("Analyze", variant="primary") | |
| gr.Markdown("""---""") | |
| gr.Markdown(f"## Data Dictionary:") | |
| gr.Markdown(""" | |
| Age : Age of the patient | |
| Sex : Sex of the patient | |
| trtbps : resting blood pressure (in mm Hg) | |
| chol : cholestoral in mg/dl fetched via BMI sensor | |
| fbs : (fasting blood sugar > 120 mg/dl) (1 = true; 0 = false) | |
| rest_ecg : resting electrocardiographic results | |
| Value 0: normal | |
| Value 1: having ST-T wave abnormality (T wave inversions and/or ST elevation or depression of > 0.05 mV) | |
| Value 2: showing probable or definite left ventricular hypertrophy by Estes' criteria | |
| thalach : maximum heart rate achieved | |
| target : 0 = less chance of heart attack 1= more chance of heart attack""") | |
| submit_btn.click( | |
| main_func, | |
| [age, sex, cp, trtbps, chol, fbs, restecg, thalachh,exng,oldpeak,slp,caa,thall], | |
| [label,local_plot], api_name="Heart_Predictor" | |
| ) | |
| demo.launch() |