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app.py

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+import gradio as gr
+import pandas as pd
+from joblib import load
+
+def cardio(age,gender,ap_hi,ap_lo,cholesterol,gluc,smoke,alco,active,height,weight):
+    model = load('cardiosight.joblib')
+    df = pd.DataFrame.from_dict(
+        {
+            "age": [age*365],
+            "gender":[0 if gender=='Male' else 1],
+            "ap_hi": [ap_hi],
+            "ap_lo": [ap_lo],
+            "cholesterol": [cholesterol + 1],
+            "gluc": [gluc + 1],
+            "smoke":[1 if smoke=='Yes' else 0],
+            "alco": [1 if alco=='Yes' else 0],
+            "active": [1 if active=='Yes' else 0],
+            "newvalues_height": [height],
+            "newvalues_weight": [weight],
+            "New_values_BMI": weight/((height/100)**2),
+            
+        }
+    )
+       
+    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 así."
+    return "Su IMC es de "+str(round(df['New_values_BMI'][0], 2))+'. '+predicted
+    
+iface = gr.Interface(
+    cardio,
+    [
+        gr.Slider(1,99,label="Age"),
+        gr.Dropdown(choices=['Male', 'Female'], label='Gender', value='Female'),
+        gr.Slider(10,250,label="Diastolic Preassure"),
+        gr.Slider(10,250,label="Sistolic Preassure"),
+        gr.Radio(["Normal","High","Very High"],type="index",label="Cholesterol"),
+        gr.Radio(["Normal","High","Very High"],type="index",label="Glucosa Level"),
+        gr.Dropdown(choices=['Yes', 'No'], label='Smoke', value='No'),
+        gr.Dropdown(choices=['Yes', 'No'], label='Alcohol', value='No'),
+        gr.Dropdown(choices=['Yes', 'No'], label='Active', value='Yes'),
+        gr.Slider(30,220,label="Height in cm"),
+        gr.Slider(10,300,label="Weight in Kg"),
+    ],
+
+    "text",
+    examples=[
+        [20,'Male',110,60,"Normal","Normal",'No','No','Yes',168,60],
+        [30,'Female',120,70,"High","High",'No','Yes','Yes',143,70],
+        [40,'Male',130,80,"Very High","Very High",'Yes','Yes','No',185,80],
+        [50,'Female',140,90,"Normal","High",'Yes','No','No',165,90],
+        [60,'Male',150,100,"High","Very High",'No','No','Yes',175,100],
+        [70,'Female',160,90,"Very High","Normal",'Yes','Yes','No',185,110],
+    ],
+    title = 'Calculadora de Riesgo Cardiovascular mediante Inteligencia Artificial',
+    description = 'Duplicación del proyecto de CARDIOSIGHT. He cambiado los botones tipo check por dropdown y calculado el IMC a partir de la altura y el peso. Más información: https://saturdays.ai/2022/03/16/cardiosight-machine-learning-para-calcular-riesgo-cardiovascular/'
+)
+
+iface.launch()

cardiosight.joblib

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+version https://git-lfs.github.com/spec/v1
+oid sha256:2be6c3effbdea5cf7b1f40ac86a2e8bd951fc60fadbf38a83c68dbd4b878f01f
+size 153988639