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README.md

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+# DATATHON_LUNG_CANCER
+DATATHON_COMPETITION

application.py

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

model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b7a60129ae21f0bef6a4ad88e7024627d4fc95d14ee3418fbcea67309dc5ea58
+size 111839

requirements.txt

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+numpy
+pandas
+scikit-learn
+imbalanced-learn
+xgboost
+matplotlib
+seaborn
+joblib
+streamlit
+streamlit-js-eval