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| import streamlit as st | |
| import requests | |
| import pandas as pd | |
| import plotly.express as px | |
| import plotly.graph_objects as go | |
| import traceback | |
| def show_liver_disease_prediction(): | |
| st.title("Liver Disease Prediction") | |
| # Create sidebar for inputs | |
| with st.sidebar: | |
| st.header("Patient Details") | |
| # Personal Information | |
| st.subheader("Personal Information") | |
| age = st.slider("Age", 10, 90, 45) | |
| gender = st.radio("Gender", ["Male", "Female"]) | |
| # Liver Function Tests | |
| st.subheader("Liver Function Tests") | |
| total_bilirubin = st.number_input("Total Bilirubin", min_value=0.1, max_value=100.0, value=1.0, step=0.1, | |
| help="Normal range: 0.3-1.2 mg/dL") | |
| direct_bilirubin = st.number_input("Direct Bilirubin", min_value=0.0, max_value=50.0, value=0.3, step=0.1, | |
| help="Normal range: 0.0-0.3 mg/dL") | |
| # Enzyme Levels | |
| st.subheader("Enzyme Levels") | |
| alkaline_phosphotase = st.number_input("Alkaline Phosphotase", min_value=20, max_value=2000, value=290, step=10, | |
| help="Normal range: 44-147 IU/L") | |
| alamine_aminotransferase = st.number_input("Alamine Aminotransferase (ALT)", min_value=1, max_value=2000, value=40, step=1, | |
| help="Normal range: 7-55 IU/L") | |
| aspartate_aminotransferase = st.number_input("Aspartate Aminotransferase (AST)", min_value=1, max_value=2000, value=40, step=1, | |
| help="Normal range: 8-48 IU/L") | |
| # Protein Levels | |
| st.subheader("Protein Levels") | |
| total_protiens = st.number_input("Total Proteins", min_value=1.0, max_value=10.0, value=6.8, step=0.1, | |
| help="Normal range: 6.0-8.3 g/dL") | |
| albumin = st.number_input("Albumin", min_value=0.5, max_value=10.0, value=3.5, step=0.1, | |
| help="Normal range: 3.5-5.0 g/dL") | |
| albumin_globulin_ratio = st.number_input("Albumin/Globulin Ratio", min_value=0.1, max_value=5.0, value=1.0, step=0.1, | |
| help="Normal range: 0.8-2.0") | |
| # Submit button | |
| predict_button = st.button("Predict Liver Disease Risk") | |
| # Main content area | |
| if predict_button: | |
| # Prepare data for API | |
| features = { | |
| "Age": age, | |
| "Gender": gender, | |
| "Total_Bilirubin": total_bilirubin, | |
| "Direct_Bilirubin": direct_bilirubin, | |
| "Alkaline_Phosphotase": alkaline_phosphotase, | |
| "Alamine_Aminotransferase": alamine_aminotransferase, | |
| "Aspartate_Aminotransferase": aspartate_aminotransferase, | |
| "Total_Protiens": total_protiens, | |
| "Albumin": albumin, | |
| "Albumin_and_Globulin_Ratio": albumin_globulin_ratio | |
| } | |
| # Call API | |
| with st.spinner("Predicting..."): | |
| try: | |
| response = requests.post( | |
| "http://localhost:8000/predict/liver", | |
| json=features | |
| ) | |
| if response.status_code == 200: | |
| result = response.json() | |
| # Display results | |
| col1, col2 = st.columns([3, 2]) | |
| with col1: | |
| # Prediction result | |
| if result["prediction"]: | |
| st.error("### High Risk of Liver Disease ⚠️") | |
| st.markdown("The patient shows indicators consistent with potential liver disease.") | |
| else: | |
| st.success("### Low Risk of Liver Disease ✅") | |
| st.markdown("The patient's indicators suggest normal liver function.") | |
| # Enhanced explanation | |
| st.info("### Key Indicators Analysis") | |
| # Create a dataframe to show normal ranges vs patient values | |
| indicators = { | |
| "Indicator": [ | |
| "Total Bilirubin", | |
| "Direct Bilirubin", | |
| "Alkaline Phosphotase", | |
| "ALT", | |
| "AST", | |
| "Total Proteins", | |
| "Albumin", | |
| "Albumin/Globulin Ratio" | |
| ], | |
| "Patient Value": [ | |
| total_bilirubin, | |
| direct_bilirubin, | |
| alkaline_phosphotase, | |
| alamine_aminotransferase, | |
| aspartate_aminotransferase, | |
| total_protiens, | |
| albumin, | |
| albumin_globulin_ratio | |
| ], | |
| "Normal Range": [ | |
| "0.3-1.2 mg/dL", | |
| "0.0-0.3 mg/dL", | |
| "44-147 IU/L", | |
| "7-55 IU/L", | |
| "8-48 IU/L", | |
| "6.0-8.3 g/dL", | |
| "3.5-5.0 g/dL", | |
| "0.8-2.0" | |
| ], | |
| "Status": [ | |
| "Normal" if 0.3 <= total_bilirubin <= 1.2 else "Abnormal", | |
| "Normal" if 0.0 <= direct_bilirubin <= 0.3 else "Abnormal", | |
| "Normal" if 44 <= alkaline_phosphotase <= 147 else "Abnormal", | |
| "Normal" if 7 <= alamine_aminotransferase <= 55 else "Abnormal", | |
| "Normal" if 8 <= aspartate_aminotransferase <= 48 else "Abnormal", | |
| "Normal" if 6.0 <= total_protiens <= 8.3 else "Abnormal", | |
| "Normal" if 3.5 <= albumin <= 5.0 else "Abnormal", | |
| "Normal" if 0.8 <= albumin_globulin_ratio <= 2.0 else "Abnormal" | |
| ] | |
| } | |
| indicators_df = pd.DataFrame(indicators) | |
| # Style the dataframe | |
| def highlight_abnormal(val): | |
| if val == "Abnormal": | |
| return 'background-color: #ffcccb' | |
| else: | |
| return 'background-color: #90ee90' | |
| styled_df = indicators_df.style.applymap(highlight_abnormal, subset=['Status']) | |
| st.dataframe(styled_df, use_container_width=True) | |
| # Feature importance visualization if available | |
| if "feature_importance" in result and result["feature_importance"]: | |
| st.subheader("Factors Affecting Liver Disease Risk") | |
| # Create feature importance dataframe | |
| feature_names = list(features.keys()) | |
| importance_values = result["feature_importance"] | |
| # If lengths don't match, use default values | |
| if len(importance_values) != len(feature_names): | |
| importance_values = [0.15, 0.05, 0.12, 0.08, 0.18, 0.14, 0.10, 0.08, 0.06, 0.04] | |
| importance_df = pd.DataFrame({ | |
| "Feature": feature_names, | |
| "Importance": importance_values | |
| }) | |
| importance_df = importance_df.sort_values("Importance", ascending=False) | |
| fig = px.bar( | |
| importance_df, | |
| x="Importance", | |
| y="Feature", | |
| orientation='h', | |
| title="Feature Importance", | |
| color="Importance", | |
| color_continuous_scale=["#90ee90", "#ffcccb"] | |
| ) | |
| st.plotly_chart(fig, use_container_width=True) | |
| # Recommendations section | |
| st.subheader("Recommendations") | |
| if result["prediction"]: | |
| st.markdown(""" | |
| * **Consult a Hepatologist:** Schedule an appointment with a liver specialist for further evaluation | |
| * **Additional Testing:** Consider ultrasound, CT scan, or liver biopsy for definitive diagnosis | |
| * **Lifestyle Changes:** | |
| * Limit alcohol consumption | |
| * Maintain a healthy weight | |
| * Follow a liver-friendly diet low in processed foods and sugar | |
| * Regular exercise | |
| * **Medication Review:** Discuss current medications with your doctor as some may affect liver function | |
| """) | |
| else: | |
| st.markdown(""" | |
| * **Regular Check-ups:** Continue routine health screenings | |
| * **Healthy Lifestyle:** | |
| * Maintain a balanced diet rich in fruits, vegetables, and whole grains | |
| * Regular physical activity | |
| * Limit alcohol consumption | |
| * Stay hydrated | |
| * **Liver Protection:** Avoid unnecessary medications that may strain the liver | |
| """) | |
| with col2: | |
| # Risk probability gauge | |
| st.subheader("Disease Risk Probability") | |
| probability = result["probability"] | |
| # Create gauge chart | |
| fig = go.Figure(go.Indicator( | |
| mode="gauge+number", | |
| value=probability * 100, | |
| domain={'x': [0, 1], 'y': [0, 1]}, | |
| title={'text': "Risk Level"}, | |
| gauge={ | |
| 'axis': {'range': [0, 100], 'tickwidth': 1}, | |
| 'bar': {'color': "darkred" if probability > 0.7 else "orange" if probability > 0.3 else "green"}, | |
| 'steps': [ | |
| {'range': [0, 30], 'color': 'rgba(0, 128, 0, 0.3)'}, | |
| {'range': [30, 70], 'color': 'rgba(255, 165, 0, 0.3)'}, | |
| {'range': [70, 100], 'color': 'rgba(255, 0, 0, 0.3)'} | |
| ], | |
| 'threshold': { | |
| 'line': {'color': "red", 'width': 4}, | |
| 'thickness': 0.75, | |
| 'value': probability * 100 | |
| } | |
| } | |
| )) | |
| fig.update_layout( | |
| height=300, | |
| margin=dict(l=20, r=20, t=50, b=20) | |
| ) | |
| st.plotly_chart(fig, use_container_width=True) | |
| # Risk level explanation | |
| risk_level = "High" if probability > 0.7 else "Moderate" if probability > 0.3 else "Low" | |
| risk_color = "red" if probability > 0.7 else "orange" if probability > 0.3 else "green" | |
| st.markdown(f"<div style='text-align: center; font-size: 24px; font-weight: bold; color: {risk_color};'>{risk_level} Risk</div>", unsafe_allow_html=True) | |
| # Liver health score | |
| st.subheader("Liver Health Indicators") | |
| # Calculate abnormal indicators | |
| abnormal_count = sum(1 for status in indicators["Status"] if status == "Abnormal") | |
| health_score = 100 - (abnormal_count / len(indicators["Status"])) * 100 | |
| # Display health score | |
| st.metric( | |
| label="Liver Health Score", | |
| value=f"{health_score:.1f}%", | |
| delta=None | |
| ) | |
| # Create progress bar for health score | |
| health_color = "green" if health_score > 70 else "orange" if health_score > 40 else "red" | |
| st.markdown(f""" | |
| <div style="width: 100%; background-color: #ddd; border-radius: 5px;"> | |
| <div style="width: {health_score}%; height: 20px; background-color: {health_color}; border-radius: 5px;"></div> | |
| </div> | |
| """, unsafe_allow_html=True) | |
| # Age and gender analysis | |
| st.subheader("Demographic Analysis") | |
| # Age risk factor | |
| age_risk = "Higher" if age > 50 else "Moderate" if age > 35 else "Lower" | |
| age_color = "red" if age > 50 else "orange" if age > 35 else "green" | |
| st.markdown(f""" | |
| <div style="margin-top: 10px;"> | |
| <span style="font-weight: bold;">Age Risk Factor:</span> | |
| <span style="color: {age_color};">{age_risk}</span> | |
| </div> | |
| """, unsafe_allow_html=True) | |
| # Gender risk factor | |
| gender_risk = "Higher" if gender == "Male" else "Lower" | |
| gender_color = "orange" if gender == "Male" else "green" | |
| st.markdown(f""" | |
| <div style="margin-top: 10px;"> | |
| <span style="font-weight: bold;">Gender Risk Factor:</span> | |
| <span style="color: {gender_color};">{gender_risk}</span> | |
| </div> | |
| <div style="margin-top: 5px; font-size: 12px; color: #888;"> | |
| Males typically have higher risk of liver disease than females. | |
| </div> | |
| """, unsafe_allow_html=True) | |
| # Disclaimer | |
| st.info("⚠️ Disclaimer: This prediction is for informational purposes only and should not replace professional medical advice.") | |
| else: | |
| st.error(f"Error: API returned status code {response.status_code}") | |
| try: | |
| error_detail = response.json() | |
| st.error(f"Error details: {error_detail}") | |
| except: | |
| st.error(response.text) | |
| except Exception as e: | |
| st.error(f"Error connecting to API: {str(e)}") | |
| st.error(traceback.format_exc()) | |
| st.info("Make sure the FastAPI backend is running with: python -m uvicorn src.api.main:app --reload") | |
| if __name__ == "__main__": | |
| show_liver_disease_prediction() |