Update model_utils.py

model_utils.py

@@ -48,7 +48,11 @@ def predict(model, img_tensor, device):
     with torch.no_grad():
         output = model(img_tensor.unsqueeze(0).to(device))
         probs = torch.sigmoid(output[0]).cpu().numpy()
-    return dict(zip(DISEASE_LIST, probs))
+    
+    # Sort all results by descending probability
+    sorted_probs = sorted(zip(DISEASE_LIST, probs), key=lambda x: x[1], reverse=True)
+    return dict(sorted_probs)
+