plot, ok and bad mental status label

app.py

@@ -320,7 +320,7 @@ def predict(
     # 'probs' is a list of arrays; each array is the prob for class=2 from each model.
     sum_prob_2 = sum(prob[0] for prob in probs if not np.isnan(prob[0]))
     sum_prob_1 = sum((1 - prob[0]) for prob in probs if not np.isnan(prob[0]))
-    severity_msg = f"{severity_base} (Sum of Prob=1={sum_prob_1:.2f}, Prob=2={sum_prob_2:.2f})"
+    severity_msg = f"{severity_base} (Sum of Prob (Bad Mental Status)={sum_prob_1:.2f}, Prob (Ok Mental Status)={sum_prob_2:.2f})"
 
     # 4) Summarize predictions (with probabilities)
     label_prediction_info = {}
@@ -358,11 +358,11 @@ def predict(
             else:
                 if pred_val == 2:
                     # Probability of class=2
-                    text_prob = f"(Prob= {prob_val_for_2:.2f} for predicted class=2)"
+                    text_prob = f"(Prob= {prob_val_for_2:.2f} for predicted class = Ok Mental Status)"
                 else:
                     # Probability of class=1
                     prob_of_1 = 1 - prob_val_for_2
-                    text_prob = f"(Prob= {prob_of_1:.2f} for predicted class=1)"
+                    text_prob = f"(Prob= {prob_of_1:.2f} for predicted class = Bad Mental Status)"
 
             # If pred_val is 1 or 2, we have a mapping
             if lbl in predictor.prediction_map and pred_val in [1, 2]: