updated feature inputs and chart..

app.py

@@ -1,82 +1,93 @@
 import gradio as gr
-import numpy as np
-import urllib.request
+import pandas as pd
+import plotly.graph_objects as go
 
-# Downloading the image and saving it in the local folder
-# urllib.request.urlretrieve('https://cdn.discordapp.com/attachments/682736875483430985/1089711182094553108/Dopeshott_young_black_femal_doctor_19e26be2-6801-4aed-b481-793b1e77a984.png', 'doctor.png')
-
-# Dummy data
-data = np.array([
-    [65, 1, 1, 1, 0.5],
-    [45, 0, 0, 0, 0.2],
-    [70, 1, 0, 1, 0.8],
-    [55, 0, 1, 0, 0.6],
-    [50, 1, 1, 1, 0.7]
-])
+data = {
+    'years_after_diagnosis': [5, 8, 7, 7, 8, 7, 5, 6, 7, 5, 6, 4, 3, 4, 5, 8, 5],
+    'age_at_diagnosis': [54, 41, 65, 85, 60, 66, 61, 50, 77, 64, 55, 52, 60, 51, 45, 54, 48],
+    'stage level': [6, 6, 5, 5, 10, 8, 6, 7, 8, 8, 3, 6, 3, 8, 6, 8, 6],
+    'status': [1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0]
+}
 
-features = ['Age', 'Sex', 'Smoking', 'Treatment', 'Chemotherapy']
-sex_options = ['Male', 'Female']
-smoking_options = ['No', 'Yes']
-treatment_options = ['No', 'Yes']
-chemo_options = ['No', 'Yes']
+df = pd.DataFrame(data)
 
-# Function to predict cancer
-def predict_cancer(age, sex, smoking, treatment, chemotherapy):
-    # Format input
-    sex = 0 if sex == 'Male' else 1
-    smoking = 0 if smoking == 'No' else 1
-    treatment = 0 if treatment == 'No' else 1
-    chemotherapy = 0 if chemotherapy == 'No' else 1
-    input_data = np.array([[age, sex, smoking, treatment, chemotherapy]])
-    # Dummy prediction
-    prob_alive = np.random.choice([0.8, 0.7, 0.65, 0.548, 0.78])
-    prediction = 'Alive' if prob_alive >= 0.5 else 'Dead'
-    return f'{prediction} with a survival probability of {prob_alive:.3f}'
+def plot_probability_chart(years_after_diagnosis, age_at_diagnosis, stage_level, chemotherapy, brachtherapy,
+                           chemoradiation, radiotherapy, radiation, menopause, MENO_post, HISTOLOGY, CM_1, CM_2, CM_3, Status):
+    match = df.loc[
+        (df['years_after_diagnosis'] == years_after_diagnosis) &
+        (df['age_at_diagnosis'] == age_at_diagnosis) &
+        (df['stage level'] == stage_level)
+    ]
+    
+    if len(match) == 0:
+        probability_alive = 0.5
+        probability_dead = 0.5
+        label = ["No matching record", "No matching record"]
+    else:   
+        status = match.iloc[0]['status']
+        label = ["Alive", "Dead"]
+        
+        if status == 0:
+            probability_alive = 0.2
+            probability_dead = 0.8
+        else:
+            probability_alive = 0.7
+            probability_dead = 0.3
 
-# Interface
-age_slider = gr.inputs.Slider(minimum=20, maximum=90, step=1, label='Age')
-sex_dropdown = gr.inputs.Dropdown(choices=sex_options, label='Sex')
-smoking_dropdown = gr.inputs.Dropdown(choices=smoking_options, label='Smoking')
-treatment_dropdown = gr.inputs.Dropdown(choices=treatment_options, label='Treatment')
-chemo_dropdown = gr.inputs.Dropdown(choices=chemo_options, label='Chemotherapy')
-inputs = [age_slider, sex_dropdown, smoking_dropdown, treatment_dropdown, chemo_dropdown]
-outputs = gr.outputs.Textbox(label='Prediction')
+    fig = go.Figure(
+        go.Bar(
+            x=label,
+            y=[probability_alive, probability_dead]
+        )
+    )
+    fig.update_layout(
+        title="Survival Probability Chart",
+        xaxis_title="Status",
+        yaxis_title="Probability",
+    )
+    return fig
+    
+    if len(match) == 0:
+        return "No matching patient record found"
+    
+    status = match.iloc[0]['status']
+    label = ["Alive", "Dead"]
+    if status == 0:
+        probability_alive = 0.2
+        probability_dead = 0.8
+    else:
+        probability_alive = 0.7
+        probability_dead = 0.3
 
-css = """
-.sidebar-content {
-    padding: 20px;
-    background-color: #f5f5f5;
-    box-shadow: 1px 1px 10px #ccc;
-    margin-bottom: 20px;
-    border-radius: 10px;
-}
-.doctor-img-container {
-    display: flex;
-    align-items: center;
-    justify-content: center;
-}
-.doctor-img {
-    height: auto;
-    width: auto;
-    max-width: 100%;
-    max-height: 100%;
-}
-"""
+    fig = go.Figure(
+        go.Bar(
+            x=label, 
+            y=[probability_alive, probability_dead]
+        )
+    )
+    fig.update_layout(
+        title="Survival Probability Chart",
+        xaxis_title="Status",
+        yaxis_title="Probability",
+    )
+    return fig
 
-sidebar = [
-    # Adding image of a doctor to the sidebar
-    '<div class="doctor-img-container"><img class="doctor-img" src="doctor.png" alt="A medical doctor"></div>',
-    'This is a cancer prediction app',
+inputs = [
+    gr.inputs.Slider(minimum=0, maximum=10, step=1, default=5, label='years_after_diagnosis'),
+    gr.inputs.Slider(minimum=0, maximum=100, step=1, default=54, label='age_at_diagnosis'),
+    gr.inputs.Slider(minimum=0, maximum=10, step=1, default=6, label='stage level'),
+    gr.inputs.Checkbox(label='chemotherapy'),
+    gr.inputs.Checkbox(label='brachtherapy'),
+    gr.inputs.Checkbox(label='chemoradiation'),
+    gr.inputs.Checkbox(label='radiotherapy'),
+    gr.inputs.Checkbox(label='radiation'),
+    gr.inputs.Slider(minimum=0, maximum=30, step=1, default=0, label='menopause'),
+    gr.inputs.Slider(minimum=0, maximum=30, step=1, default=0, label='MENO_post'),
+    gr.inputs.Slider(minimum=0, maximum=2, step=1, default=2, label='HISTOLOGY'),
+    gr.inputs.Checkbox(label='CM_1'),
+    gr.inputs.Checkbox(label='CM_2'),
+    gr.inputs.Checkbox(label='CM_3'),
+    gr.inputs.Radio(["Alive", "Dead"], label="Status")
 ]
 
-iface = gr.Interface(
-    fn=predict_cancer,
-    inputs=inputs,
-    outputs=outputs,
-    title='Cancer Predictor',
-    description='Predicts the risk of survival in cancer patients.\nChoose the input values and the prediction will be displayed automatically.',
-    sidebar=sidebar,
-    css=css
-)
-
-iface.launch()
+gr.Interface(fn=plot_probability_chart, inputs=inputs, outputs="plot").launch()