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import streamlit as st
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import pandas as pd
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import joblib
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model = joblib.load('model.pkl')
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st.title('🫁 Lung Cancer Diagnosis')
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st.write("Please fill out the following information to assess the likelihood of lung cancer.")
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gender = st.selectbox('Gender', [0, 1], format_func=lambda x: "Female" if x == 0 else "Male")
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age = st.number_input('Age', max_value=120, value=0)
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smoking = st.selectbox('Smoking', ['Yes', 'No'])
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yellow_fingers = st.selectbox('Yellow Fingers', ['Yes', 'No'])
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anxiety = st.selectbox('Anxiety', ['Yes', 'No'])
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peer_pressure = st.selectbox('Peer Pressure', ['Yes', 'No'])
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chronic_disease = st.selectbox('Chronic Disease', ['Yes', 'No'])
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fatigue = st.selectbox('Fatigue', ['Yes', 'No'])
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allergy = st.selectbox('Allergy', ['Yes', 'No'])
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wheezing = st.selectbox('Wheezing', ['Yes', 'No'])
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alcohol = st.selectbox('Alcohol Consuming', ['Yes', 'No'])
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coughing = st.selectbox('Coughing', ['Yes', 'No'])
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shortness_of_breath = st.selectbox('Shortness of Breath', ['Yes', 'No'])
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swallowing_difficulty = st.selectbox('Swallowing Difficulty', ['Yes', 'No'])
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chest_pain = st.selectbox('Chest Pain', ['Yes', 'No'])
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def binary_encode(value):
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return 1 if value == 'Yes' else 0
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data = pd.DataFrame([[
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gender,
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age,
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binary_encode(smoking),
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binary_encode(yellow_fingers),
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binary_encode(anxiety),
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binary_encode(peer_pressure),
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binary_encode(chronic_disease),
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binary_encode(fatigue),
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binary_encode(allergy),
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binary_encode(wheezing),
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binary_encode(alcohol),
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binary_encode(coughing),
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binary_encode(shortness_of_breath),
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binary_encode(swallowing_difficulty),
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binary_encode(chest_pain)
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]], columns=[
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'GENDER', 'AGE', 'SMOKING', 'YELLOW_FINGERS', 'ANXIETY', 'PEER_PRESSURE',
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'CHRONIC DISEASE', 'FATIGUE', 'ALLERGY', 'WHEEZING', 'ALCOHOL CONSUMING',
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'COUGHING', 'SHORTNESS OF BREATH', 'SWALLOWING DIFFICULTY', 'CHEST PAIN'
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])
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if st.button('Predict'):
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prediction = model.predict(data)[0]
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if prediction == 1:
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st.error("⚠️ High risk of lung cancer. Please consult a doctor.")
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else:
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st.success("✅ No Lung Cancer.")
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