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import gradio as gr
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
def hazard_predictor(gender, age, bmi, diabetes_type, spb, dbp, hba1c, smoking, marital_status):
# Dummy hazard function with a limit of 0.95 (95%)
hazard_ratio = min((age / 50) * (bmi / 25) * (spb / 120) * (dbp / 80), 0.92)
return {'Hazard Ratio': hazard_ratio}
def plot_chart(hazard_ratio, age):
age_range = np.linspace(18, 100, 500)
hazard_ratio_line = []
for a in age_range:
if a <= age:
hazard_ratio_line.append(a / age * hazard_ratio)
else:
hazard_ratio_line.append(hazard_ratio)
# Create a dataframe for Seaborn plotting
data = {'Age': age_range, 'Hazard Ratio': hazard_ratio_line}
df = pd.DataFrame(data)
# Create the Seaborn line plot
sns_plot = sns.lineplot(x="Age", y="Hazard Ratio", data=df)
# Set plot labels and limits
sns_plot.set(xlabel='Age', ylabel='Hazard Ratio', ylim=(0, 1))
# Save the plot as an image
chart_filepath = "chart.png"
plt.savefig(chart_filepath, dpi=150)
plt.close() # Close the plot to free up the memory
return chart_filepath
def output_function(gender, age, bmi, diabetes_type, spb, dbp, hba1c, smoking, marital_status):
hazard_ratio = hazard_predictor(gender, age, bmi, diabetes_type, spb, dbp, hba1c, smoking, marital_status)['Hazard Ratio']
output_label = f"Hazard Ratio: {hazard_ratio}"
chart_filepath = plot_chart(hazard_ratio, age)
return output_label, chart_filepath
# Save the chart as an image
chart_filepath = "chart.png"
chart.savefig(chart_filepath, dpi=150)
return output_label, chart_filepath
# Gradio user interface components
gender_radio = gr.inputs.Radio(choices=['Female', 'Male'], label="Gender")
age_slider = gr.inputs.Slider(minimum=18, maximum=100, step=1, default=50, label="Age")
bmi_slider = gr.inputs.Slider(minimum=15, maximum=50, step=0.1, default=25, label="BMI")
diabetes_type_radio = gr.inputs.Radio(choices=['Type 1', 'Type 2', 'Gestational'], label="Diabetes Type")
spb_slider = gr.inputs.Slider(minimum=90, maximum=200, step=1, default=120, label="Systolic Blood Pressure (SPB)")
dbp_slider = gr.inputs.Slider(minimum=60, maximum=120, step=1, default=80, label="Diastolic Blood Pressure (DBP)")
hba1c_slider = gr.inputs.Slider(minimum=100, maximum=400, step=1, default=200, label="Hemoglobin A1c value (mg/dL)")
smoking_radio = gr.inputs.Radio(choices=['Non-smoker', 'Smoker'], label="Smoking History")
marital_status_dropdown = gr.inputs.Dropdown(choices=['Single', 'Married', 'Widowed', 'Divorced'], label="Marital Status")
output_text = gr.outputs.Textbox(label="Hazard Ratio")
output_chart = gr.outputs.Image(type='filepath')
# Creating Gradio interface
interface = gr.Interface(fn=output_function,
inputs=[gender_radio, age_slider, bmi_slider, diabetes_type_radio, spb_slider, dbp_slider, hba1c_slider, smoking_radio, marital_status_dropdown],
outputs=[output_text, output_chart],
title="Diabetes Cox Proportional Hazard Predictor",
submit_button="Predict")
interface.launch(debug=True) |