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import gradio as gr | |
import pandas as pd | |
from joblib import load | |
def cardio(age,is_male,ap_hi,ap_lo,cholesterol,gluc,smoke,alco,active,height,weight,BMI): | |
model = load('cardiosight.joblib') | |
df = pd.DataFrame.from_dict( | |
{ | |
"age": [age*365], | |
"gender":[0 if is_male else 1], | |
"ap_hi": [ap_hi], | |
"ap_lo": [ap_lo], | |
"cholesterol": [cholesterol + 1], | |
"gluc": [gluc + 1], | |
"smoke":[1 if smoke else 0], | |
"alco": [1 if alco else 0], | |
"active": [1 if active else 0], | |
"newvalues_height": [height], | |
"newvalues_weight": [weight], | |
"New_values_BMI": [BMI], | |
} | |
) | |
pred = model.predict(df)[0] | |
if pred==1: | |
predicted="Tiene un riesgo alto de sufrir problemas cardiovasculares" | |
else: | |
predicted="Su riesgo de sufrir problemas cardiovasculares es muy bajo. Siga as铆." | |
return predicted | |
iface = gr.Interface( | |
cardio, | |
[ | |
gr.inputs.Slider(1,99,label="Age"), | |
"checkbox", | |
gr.inputs.Slider(10,250,label="Diastolic Preassure"), | |
gr.inputs.Slider(10,250,label="Sistolic Preassure"), | |
gr.inputs.Radio(["Normal","High","Very High"],type="index",label="Cholesterol"), | |
gr.inputs.Radio(["Normal","High","Very High"],type="index",label="Glucosa Level"), | |
"checkbox", | |
"checkbox", | |
"checkbox", | |
gr.inputs.Slider(30,220,label="Height in cm"), | |
gr.inputs.Slider(10,300,label="Weight in Kg"), | |
gr.inputs.Slider(1,50,label="BMI"), | |
], | |
"text", | |
examples=[ | |
[40,True,120,80,"High","Normal",0,0,1,168,62,21], | |
[35,False,150,60,"Very High","Normal",0,0,1,143,52,31], | |
[60,True,160,70,"High","High",1,1,0,185,90,23], | |
], | |
interpretation="default", | |
title = 'Calculadora de Riesgo Cardiovascular mediante Inteligencia Artificial', | |
description = 'El proyecto de CARDIOSIGHT nace debido a la presente necesidad en nuestro pa铆s de crear m茅todos y herramientas de identificaci贸n temprana para los individuos con alto riesgo de sufrir enfermedades cardiovasculares. Con el fin de prevenir eventos card铆acos primarios y ayudar a disminuir la incidencia de nuevos casos, por medio de h谩bitos de prevenci贸n. Mas informaci贸n: https://saturdays.ai/2022/03/16/cardiosight-machine-learning-para-calcular-riesgo-cardiovascular/', | |
theme = 'grass' | |
) | |
iface.launch() |