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import gradio as gr
import joblib as jb
import pandas as pd
pipe = jb.load('heart1.pkl')
def predict(age, sex, cp, trtbps, chol, fbs, restecg, thalachh, exng, oldpeak, slp, caa, thall):
if sex=="Male":
sex=1
else:
sex=0
if cp=="Typical Angina":
cp=0
elif cp=="Typical Angina":
cp=1
elif cp=="Atypical Angina":
cp=2
elif cp=="Non-Anginal pain":
cp=3
elif cp=="Asymptomatic":
cp=4
else:
cp=0
if fbs>120:
fbs=1
else:
fbs=0
if restecg=="Normal":
restecg=0
elif restecg=="ST-T wave abnormality":
restecg=1
elif restecg=="Definite left Ventricular hypertrophy":
restecg=2
else:
restecg=0
if slp=="Unsloping":
slp=0
elif restecg=="flat":
slp=1
elif restecg=="Downsloping":
slp=2
else:
slp=0
if exng=="Yes":
exng=1
else:
exng=0
if thall=="Null":
thall=0
elif thall=="Fixed defect":
thall=1
elif cp=="Normal":
thall=2
elif cp=="Reversable defect":
thall=3
else:
thall=0
x = pd.DataFrame([[age, sex, cp, trtbps, chol, fbs, restecg, thalachh, exng, oldpeak, slp, caa, thall]])
x.columns = ["age", "sex", "cp", "trtbps", "chol", "fbs", "restecg", "thalachh", "exng", "oldpeak", "slp", "caa", "thall"]
prediction = pipe.predict(x)
ans = prediction[0]
if ans>=1:
ans = 100
elif ans<=0:
ans = 0
else:
ans = ans*100
if ans>50:
final = str(int(ans)) + "%" +"\n>50% Diameter narrowing.\nMore chance of heart disease."
else:
final = str(int(ans)) + "%" + "\n< 50% Diameter narrowing.\nLess chance of heart disease."
return final
app = gr.Interface(title="Heart Attack Predictor",fn=predict,
inputs=[
gr.inputs.Number(label='Age'),
gr.inputs.Radio(["Male","Female"],label='Sex'),
gr.inputs.Radio(["Typical Angina","Atypical Angina","Non-Anginal pain","Asymptomatic"],label='Chest Pain'),
gr.inputs.Number(label='Resting blood pressure (in mm Hg)'),
gr.inputs.Number(label='Cholestoral in mg/dl '),
gr.inputs.Number(label='Fasting blood sugar'),
gr.inputs.Radio(["Normal","ST-T wave abnormality","Definite left Ventricular hypertrophy"],label='Resting Rlectrocardiographic Results'),
gr.inputs.Number(label='Maximum Heartrate achieved'),
gr.inputs.Radio(["Yes","No"],label='Exercise induced Angina'),
gr.inputs.Number(label='ST depression induced by exercise'),
gr.inputs.Radio(["Unsloping","flat","Downsloping"],label='Slope of the peak exercise ST segment'),
gr.inputs.Slider(minimum=0,maximum=3,step=1,label='Number of major vessels'),
gr.inputs.Radio(["Null","Fixed defect","Normal","Reversable defect"],label='Thalassemia'),
],
outputs=gr.outputs.Textbox(label="Prediction")
)
app.launch()
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