import streamlit as st
import joblib
import pandas as pd

# Modeli yükle
model = joblib.load('thyroid_cancer_model.pkl')

# Uygulama başlığı
st.title('Thyroid Cancer Recurrence Prediction')

# Giriş verilerini al
age = st.number_input('Age', min_value=0, max_value=100, step=1)
gender = st.selectbox('Gender', ['M', 'F'])
smoking = st.selectbox('Smoking', ['Yes', 'No'])
hx_smoking = st.selectbox('Hx Smoking', ['Yes', 'No'])
hx_radiotherapy = st.selectbox('Hx Radiotherapy', ['Yes', 'No'])
thyroid_function = st.selectbox('Thyroid Function', ['Euthyroid', 'Clinical Hyperthyroidism', 'Subclinical Hyperthyroidism'])
physical_examination = st.selectbox('Physical Examination', ['Single nodular goiter-left', 'Multinodular goiter', 'Single nodular goiter-right'])
adenopathy = st.selectbox('Adenopathy', ['No', 'Right', 'Left', 'Bilateral', 'Extensive'])
pathology = st.selectbox('Pathology', ['Micropapillary', 'Papillary', 'Follicular', 'Hurthel cell'])
focality = st.selectbox('Focality', ['Uni-Focal', 'Multi-Focal'])
risk = st.selectbox('Risk', ['Low', 'Intermediate', 'High'])
t = st.selectbox('T', ['T1a', 'T1b', 'T2', 'T3', 'T4a', 'T4b'])
n = st.selectbox('N', ['N0', 'N1a', 'N1b'])
m = st.selectbox('M', ['M0', 'M1'])
stage = st.selectbox('Stage', ['I', 'II', 'III', 'IVA', 'IVB'])
response = st.selectbox('Response', ['Excellent', 'Indeterminate', 'Biochemical Incomplete', 'Structural Incomplete'])

# Giriş verilerini bir dataframe'e dönüştür
input_data = pd.DataFrame({
    'Age': [age],
    'Gender': [gender],
    'Smoking': [smoking],
    'Hx Smoking': [hx_smoking],
    'Hx Radiothreapy': [hx_radiotherapy],
    'Thyroid Function': [thyroid_function],
    'Physical Examination': [physical_examination],
    'Adenopathy': [adenopathy],
    'Pathology': [pathology],
    'Focality': [focality],
    'Risk': [risk],
    'T': [t],
    'N': [n],
    'M': [m],
    'Stage': [stage],
    'Response': [response]
})

# Tahmin yap butonu
if st.button('Predict Recurrence'):
    prediction = model.predict(input_data)
    result = 'likely to recur' if prediction[0] == 1 else 'not likely to recur'
    st.write(f'The model predicts that the cancer is {result}.')