Update app.py

app.py

@@ -187,29 +187,12 @@ output_y4 = (
 
 
 #Define predict for y1.
-def bootstrap_ci(data, model, alpha=0.05):
-    """Compute bootstrap confidence intervals"""
-    bootstrapped_probs = [model.predict_proba(resample(data))[0][1] for _ in range(100)]
-    lower = np.percentile(bootstrapped_probs, 100*(alpha/2.0))
-    upper = np.percentile(bootstrapped_probs, 100*(1-alpha/2.0))
-    return lower, upper
-
 def y1_predict(*args):
     df1 = pd.DataFrame([args], columns=x1.columns)
     pos_pred = y1_calib_model.predict_proba(df1)
     prob = pos_pred[0][1]
-    prob = 1 - prob
-    lower, upper = bootstrap_ci(df1, y1_calib_model)
-    output = (
-        f"""
-        <br/>
-        <center>The probability of 6-month survival:</center>
-        <br/>
-        <center><h1>{prob:.2f}%</h1></center>
-        <br/>
-        <center>95% Confidence Interval: [{lower:.2f}%, {upper:.2f}%]</center>
-        """
-    )
+    prob = 1-prob
+    output = output_y1.format(prob * 100)
     return output
 
 #Define predict for y2.