Upload app.py

app.py

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+
+import streamlit as st
+import pandas as pd
+import joblib
+import numpy as np
+
+model = joblib.load("model/xgb_model.joblib")
+scaler = joblib.load("model/scaler.joblib")
+
+st.title("Hemoglobin Level Predictor")
+
+st.markdown(
+    '''
+    ### Developed by Dr. Vinod Kumar Yata's research group  
+    School of Allied and Healthcare Sciences, Malla Reddy University, Hyderabad, India
+
+    ---
+    ⚠️ **Warning**:  
+    This is an experimental tool and should not be used for medical diagnosis.  
+    Always consult a licensed healthcare provider for medical advice.
+    ---
+    ''',
+    unsafe_allow_html=True
+)
+
+age = st.number_input("Age", min_value=0, max_value=120, value=30)
+gender = st.selectbox("Gender", options=["Male", "Female"])
+o2_saturation = st.slider("O2 Saturation (%)", min_value=50.0, max_value=100.0, value=98.0)
+bp_systolic = st.number_input("Systolic BP", min_value=50, max_value=200, value=120)
+bp_diastolic = st.number_input("Diastolic BP", min_value=30, max_value=130, value=80)
+respiratory_rate = st.number_input("Respiratory Rate (breaths/min)", min_value=5, max_value=60, value=18)
+
+gender_num = 1 if gender == "Male" else 0
+
+input_df = pd.DataFrame([{
+    "Age": age,
+    "Gender": gender_num,
+    "O2_Saturation": o2_saturation,
+    "BP_Systolic": bp_systolic,
+    "BP_Diastolic": bp_diastolic,
+    "Respiratory_Rate": respiratory_rate
+}])
+
+if st.button("Predict Hemoglobin Level"):
+    input_scaled = scaler.transform(input_df)
+    prediction = model.predict(input_scaled)[0]
+    st.success(f"Predicted Hemoglobin Level: {prediction:.2f} g/dL")