Update app.py

app.py

@@ -77,7 +77,7 @@ def predict_icd(text_input, model_name, label_count):
         labels  = ['038.9', '244.9', '250.00', '272.0', '272.4', '276.1', '276.2', '285.1', '285.9', '287.5', '305.1', '311', '33.24', '36.15', '37.22', '38.91', '38.93', '39.61', '39.95', '401.9', '403.90', '410.71', '412', '414.01', '424.0', '427.31', '428.0', '45.13', '486', '496', '507.0', '511.9', '518.81', '530.81', '584.9', '585.9', '599.0', '88.56', '88.72', '93.9', '96.04', '96.6', '96.71', '96.72', '99.04', '99.15', '995.92', 'V15.82', 'V45.81', 'V58.61']
         values = [0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0]
     if label_count == "5":
-        labels = ['38.93', '401.90', '414.01', '427.31', '428.00']
+        labels = ['38.93', '401.9', '414.01', '427.31', '428.0']
         values = [1, 0, 0, 0, 0]
     label_map = {i: label for i, label in enumerate(labels)}
     data_dict = {label: [] for label in labels}