Update app.py

app.py

@@ -25,6 +25,13 @@ def predict_sepsis(input_data):
     prediction = model.predict(input_scaled_df)[0]
     probabilities = model.predict_proba(input_scaled_df)[0]
     sepsis_status = "Positive" if prediction == 1 else "Negative"
+    
+    if prediction == 1:
+        status_icon = "✔"  # Red 'X' icon for positive sepsis prediction
+        sepsis_explanation = "Sepsis is a life-threatening condition caused by an infection. A positive prediction suggests that the patient might be exhibiting sepsis symptoms and requires immediate medical attention."
+    else:
+        status_icon = "✘"  # Green checkmark icon for negative sepsis prediction
+        sepsis_explanation = "Sepsis is a life-threatening condition caused by an infection. A negative prediction suggests that the patient is not currently exhibiting sepsis symptoms."
 
     output_df = pd.DataFrame(input_data, columns=['PRG', 'PL', 'PR', 'SK', 'TS', 'M11', 'BD2', 'Age', 'Insurance'])
     output_df['Prediction'] = sepsis_status
@@ -104,7 +111,6 @@ def main():
             st.pyplot(fig)
 
             # Print feature importance
-
             if hasattr(model, 'coef_'):
                 feature_importances = model.coef_[0]
                 feature_names = ['PRG', 'PL', 'PR', 'SK', 'TS', 'M11', 'BD2', 'Age', 'Insurance']
@@ -129,11 +135,12 @@ def main():
                     ha='center', va='bottom')
                 st.pyplot(fig)
 
-
-                #st.subheader('Feature Importance')
-                #st.write(importance_df)
             else:
                 st.write('Feature importance is not available for this model.')
 
+            st.subheader('Sepsis Explanation')
+            st.markdown(f"{status_icon} {sepsis_explanation}")
+
+
 if __name__ == '__main__':
     main()