Update app.py

app.py

@@ -37,19 +37,28 @@ def predict_lung_cancer(GENDER, AGE, SMOKING, YELLOW_FINGERS, ANXIETY, PEER_PRES
                          FATIGUE, ALLERGY, WHEEZING, ALCOHOL_CONSUMING, COUGHING, SHORTNESS_OF_BREATH, 
                          SWALLOWING_DIFFICULTY, CHEST_PAIN):
     
-    gender_value = 0 if GENDER == "Male" else 1
-    feature_values = [gender_value, AGE] + [1 if x == "Yes" else 0 for x in [
-        SMOKING, YELLOW_FINGERS, ANXIETY, PEER_PRESSURE, CHRONIC_DISEASE, 
-        FATIGUE, ALLERGY, WHEEZING, ALCOHOL_CONSUMING, COUGHING, SHORTNESS_OF_BREATH, 
-        SWALLOWING_DIFFICULTY, CHEST_PAIN
-    ]]
+    # Gender Encoding: Male -> 0, Female -> 1
+    gender_value = 0 if GENDER.lower() == "male" else 1
     
+    # Convert "Yes" -> 1, "No" -> 0
+    feature_values = [gender_value, AGE] + [
+        1 if x.lower() == "yes" else 0 for x in [
+            SMOKING, YELLOW_FINGERS, ANXIETY, PEER_PRESSURE, CHRONIC_DISEASE, 
+            FATIGUE, ALLERGY, WHEEZING, ALCOHOL_CONSUMING, COUGHING, SHORTNESS_OF_BREATH, 
+            SWALLOWING_DIFFICULTY, CHEST_PAIN
+        ]
+    ]
+    
+    # Convert to NumPy array and Reshape
     features = np.array([feature_values])
+    
+    # **Apply the same scaling transformation used during training**
     features_scaled = scaler.transform(features)
+    
+    # **Predict using the trained model**
     prediction = model.predict(features_scaled)
     
     return "Lung Cancer Detected" if prediction[0] == 1 else "No Lung Cancer"
-
 # Create GUI with Gradio
 with gr.Blocks() as demo:
     gr.Markdown("# 🩺 Lung Cancer Detection AI")