Spaces:
Sleeping
Sleeping
File size: 2,427 Bytes
55f664e 98a0238 b565f0a c48f883 98a0238 b565f0a 98a0238 b565f0a 98a0238 c48f883 98a0238 c48f883 98a0238 c48f883 98a0238 c48f883 98a0238 c48f883 98a0238 c48f883 98a0238 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 |
import gradio as gr
import joblib
import numpy as np
# Load the trained model
model = joblib.load("trained_model.pkl")
# Define the prediction function
def predict_heart_disease(
PhysicalHealthDays: float,
MentalHealthDays: float,
SleepHours: float,
BMI: float,
PhysicalActivities: str,
AlcoholDrinkers: str,
HIVTesting: str,
RemovedTeeth: str,
HighRiskLastYear: str,
CovidPos: str,
):
try:
# Encode categorical inputs as integers
physical_activities = 1 if PhysicalActivities == "Yes" else 0
alcohol_drinkers = 1 if AlcoholDrinkers == "Yes" else 0
hiv_testing = 1 if HIVTesting == "Yes" else 0
removed_teeth = 1 if RemovedTeeth == "Yes" else 0
high_risk_last_year = 1 if HighRiskLastYear == "Yes" else 0
covid_pos = 1 if CovidPos == "Yes" else 0
# Prepare features as a numpy array
features = np.array([[
PhysicalHealthDays,
MentalHealthDays,
SleepHours,
BMI,
physical_activities,
alcohol_drinkers,
hiv_testing,
removed_teeth,
high_risk_last_year,
covid_pos,
]])
# Make prediction
prediction = model.predict(features)
result = "Yes" if prediction[0] == 1 else "No"
return f"Heart Disease Prediction: {result}"
except Exception as e:
return f"Error in prediction: {str(e)}"
# Define the Gradio interface
inputs = [
gr.inputs.Number(label="Physical Health Days"),
gr.inputs.Number(label="Mental Health Days"),
gr.inputs.Number(label="Sleep Hours"),
gr.inputs.Number(label="BMI"),
gr.inputs.Radio(["Yes", "No"], label="Physical Activities"),
gr.inputs.Radio(["Yes", "No"], label="Alcohol Drinkers"),
gr.inputs.Radio(["Yes", "No"], label="HIV Testing"),
gr.inputs.Radio(["Yes", "No"], label="Removed Teeth"),
gr.inputs.Radio(["Yes", "No"], label="High Risk Last Year"),
gr.inputs.Radio(["Yes", "No"], label="Covid Positive"),
]
outputs = gr.outputs.Textbox(label="Heart Disease Prediction")
# Create the Gradio app
app = gr.Interface(
fn=predict_heart_disease,
inputs=inputs,
outputs=outputs,
title="Heart Disease Prediction App",
description="Please enter health metrics to predict the risk of heart disease."
)
# Launch the app
if __name__ == "__main__":
app.launch()
|