prediction / app.py
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Update app.py
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import gradio as gr
import numpy as np
import matplotlib.pyplot as plt
# Function to simulate blood glucose changes over time
def predict_glucose(current_glucose, meal_type, meal_time_hr, meal_time_min, galvus_dose, galvus_time_hr, galvus_time_min, exercise_duration, fast_carbs_ml, chocolate_time_min, prediction_time=3):
# Constants for glucose reduction effects
post_meal_reduction = 63.6 # mg/dL (avg reduction for Vildagliptin in 2 hours)
fasting_reduction = 27.7 # mg/dL (avg reduction over 6-12 hours)
# Convert meal time and Galvus time to minutes for easier calculations
meal_time_total_min = meal_time_hr * 60 + meal_time_min
galvus_time_total_min = galvus_time_hr * 60 + galvus_time_min
# Adjust for fast carbs (milk, juice, etc.)
carb_effect = fast_carbs_ml * 1.5 # Approximate glucose rise per mL of fast carbs
# Calculate blood glucose over time considering meal type, Galvus dose, and exercise
if meal_type == 'High-carb':
glucose_after_meal = current_glucose + carb_effect + 60 # Higher glucose increase due to carbs
elif meal_type == 'Protein-heavy':
glucose_after_meal = current_glucose + 20 # Small glucose increase due to protein
elif meal_type == 'Low-carb':
glucose_after_meal = current_glucose - 10 # Small reduction due to low-carb meal
elif meal_type == 'Fast carb':
glucose_after_meal = current_glucose + carb_effect * 1.5 # Fast carbs like juice, milk increase glucose quickly
else:
glucose_after_meal = current_glucose # Normal meal with moderate carbs
# Calculate glucose levels over 1 hour and 3 hours
glucose_1hr = glucose_after_meal - post_meal_reduction + carb_effect * 0.5 # Adjust for carb effect
glucose_3hr = glucose_1hr - fasting_reduction
# Adjust the effects of Galvus based on its administration time (medication effect starts at galvus_time + 1-2 hours)
time_since_galvus = meal_time_total_min - galvus_time_total_min
if time_since_galvus >= 60: # After 1 hour, the effects of Galvus start kicking in
glucose_3hr -= fasting_reduction # Galvus effect after 3 hours
# Exercise effect on glucose (hypothetical value, may vary based on intensity)
glucose_3hr -= exercise_duration * 2 # Exercise reduces glucose by 2 mg/dL per minute
# Chocolate bar effect
if chocolate_time_min <= 60: # If the chocolate bar is eaten within 1 hour
glucose_1hr += 40 # Approximate glucose rise from chocolate
glucose_3hr += 30 # This would still contribute to an increase at 3 hours
# Plotting the graph of glucose prediction over time
time_points = [0, 1, 3] # Time: 0 hours, 1 hour, 3 hours
glucose_values = [current_glucose, glucose_1hr, glucose_3hr]
plt.plot(time_points, glucose_values, marker='o', color='b')
plt.title("Blood Glucose Prediction Over Time")
plt.xlabel("Time (Hours)")
plt.ylabel("Blood Glucose (mg/dL)")
plt.xticks([0, 1, 2, 3])
plt.grid(True)
plt.tight_layout()
# Save the graph as a file to show it in Gradio
plt.savefig('/tmp/blood_glucose_prediction.png')
plt.close()
# Return glucose predictions and the image file path
return glucose_1hr, glucose_3hr, '/tmp/blood_glucose_prediction.png'
# Gradio Interface
def build_interface():
with gr.Blocks() as iface:
gr.Markdown("# Blood Glucose Prediction Model (With Vildagliptin Effects)")
# Inputs for current glucose, meal info, medication dose, exercise, fast carbs, and Galvus time
with gr.Row():
current_glucose = gr.Number(label="Current Blood Glucose (mg/dL)", value=105)
meal_type = gr.Radio(choices=["Normal", "High-carb", "Protein-heavy", "Low-carb", "Fast carb"], label="Meal Type", value="Low-carb")
meal_time_hr = gr.Number(label="Last Meal Time (hours)", value=6)
meal_time_min = gr.Number(label="Last Meal Time (minutes)", value=0)
galvus_dose = gr.Number(label="Galvus Dose (mg)", value=50)
galvus_time_hr = gr.Number(label="Galvus Time of Administration (hours)", value=2)
galvus_time_min = gr.Number(label="Galvus Time of Administration (minutes)", value=0)
exercise_duration = gr.Number(label="Exercise Duration (min)", value=60)
fast_carbs_ml = gr.Number(label="Fast Carbs (mL)", value=0)
chocolate_time_min = gr.Number(label="Time After Meal When Chocolate Bar Is Eaten (min)", value=60)
# Output predictions and graph
glucose_1hr_output = gr.Textbox(label="Predicted Glucose Level in 1 Hour (mg/dL)")
glucose_3hr_output = gr.Textbox(label="Predicted Glucose Level in 3 Hours (mg/dL)")
glucose_graph = gr.Image(label="Blood Glucose Prediction Graph")
# Button to trigger prediction
predict_button = gr.Button("Predict Blood Glucose")
# Set button action
predict_button.click(
predict_glucose,
inputs=[current_glucose, meal_type, meal_time_hr, meal_time_min, galvus_dose, galvus_time_hr, galvus_time_min, exercise_duration, fast_carbs_ml, chocolate_time_min],
outputs=[glucose_1hr_output, glucose_3hr_output, glucose_graph]
)
return iface
# Build and launch the Gradio interface
iface = build_interface()
iface.launch()