Refactor sidebar options and update diabetes prediction logic to handle gender-specific input

app.py

@@ -62,7 +62,7 @@ with st.sidebar:
     
     selected = option_menu(
         menu_title="Navigation",
-        options=['Home',  'Diabetes Prediction','Hypertension Prediction', 'Cardiovascular Disease Prediction', 'Stroke Prediction','Asthma Prediction', 'Sleep Health Analysis','Mental-Analysis','Medical Consultant', 'Data Visualization'],
+        options=['Home',  'Diabetes Prediction','Hypertension Prediction', 'Cardiovascular Disease Prediction', 'Asthma Prediction', 'Sleep Health Analysis','Mental-Analysis','Medical Consultant', 'Data Visualization'],
         icons=['house', 'activity', 'lungs', 'heart-pulse', 'brain', 'bar-chart', 'chat'],
         menu_icon="cast",
         default_index=0,
@@ -74,7 +74,7 @@ with st.sidebar:
         }
     )
 
-
+# 'Stroke Prediction',
 # 'Checkbox-to-disease-predictor', 
 # 'Text-based Disease Prediction', 
 # Utility function to safely convert input to float
@@ -152,7 +152,15 @@ if selected == 'Diabetes Prediction':
     col1, col2 = st.columns(2)
 
     with col1:
-        Pregnancies = safe_float(st.text_input("Number of Pregnancies", "0"))
+        gender = st.radio("Gender", ["Male", "Female"], horizontal=True)
+        
+        # For females, show Pregnancies input; for males, set to 0
+        if gender == "Female":
+            Pregnancies = safe_float(st.text_input("Number of Pregnancies", "0"))
+        else:
+            Pregnancies = 0.0
+            st.info("Pregnancies set to 0 for males")
+            
         Glucose = safe_float(st.text_input("Glucose Level", "100"))
         BloodPressure = safe_float(st.text_input("Blood Pressure", "80"))
         SkinThickness = safe_float(st.text_input("Skin Thickness", "20"))
@@ -171,13 +179,13 @@ if selected == 'Diabetes Prediction':
                 with st.spinner("⏳ Predicting... Please wait..."):
                     time.sleep(2)  # Simulating delay (remove in actual use)
                     diab_prediction = diabetes_model.predict(input_data)
-
-                
                 
                 result = "🛑 The person is diabetic" if diab_prediction[0] == 1 else "✅ The person is not diabetic"
                 if diab_prediction[0] == 0:
                     # st.balloons()  # Or use st.confetti() if you install the library
                     st.success(result)
+                else:
+                    st.error(result)
 
             except Exception as e:
                 st.error(f"❌ Error: {e}")

requirements.txt

@@ -4,6 +4,8 @@ streamlit
 streamlit-option-menu
 seaborn
 matplotlib
+pickle5
+joblib
 pandas
 google-generativeai
 python-dotenv
@@ -15,3 +17,4 @@ tf-keras
 plotly
 plotly-express
 xgboost
+scikit-learn-extra