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app.py

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+import numpy as np
+#import pandas as pd
+#from sklearn.preprocessing import MinMaxScaler, OneHotEncoder, PowerTransformer, OrdinalEncoder
+from sklearn.compose import ColumnTransformer
+from sklearn.pipeline import Pipeline
+from sklearn.metrics import accuracy_score, confusion_matrix, ConfusionMatrixDisplay
+from sklearn.ensemble import RandomForestClassifier
+import streamlit as st
+import pickle
+
+# Page configuration
+st.set_page_config(page_title="Heart Disease Prediction App", page_icon="\u2764\ufe0f", layout="wide")
+
+# Custom styles
+st.markdown(
+    """
+    <style>
+    .main {background-color: #f0f2f6;}
+    h1 {color: #d63384; text-align: center; font-family: 'Arial', sans-serif;}
+    .stButton > button {background-color: #d63384; color: white; border-radius: 10px;}
+    .stButton > button:hover {background-color: #a02364;}
+    </style>
+    """,
+    unsafe_allow_html=True,
+)
+
+# Header
+st.title("\u2764\ufe0f Heart Disease Prediction App \u2764\ufe0f")
+st.image("https://huggingface.co/spaces/Abhisikta-26201/Heart_Disease_Classification/resolve/main/IMG_20241212_011225.jpg", use_container_width=True)
+
+# Input fields
+with st.form("input_form"):
+    st.header("Enter Patient Information")
+
+    # Column layout for inputs
+    col1, col2 = st.columns(2)
+
+    with col1:
+        age = st.number_input("Age", min_value=0, max_value=120, step=1, format="%d", help="Enter the age of the patient (in Years)")
+        gender = st.radio("Gender", ['Male', 'Female'], horizontal=True, help="Select the patient's gender")
+        chestpain = st.selectbox(
+            "Chest Pain Type",
+            ['No Data Available','Non-anginal_pain', 'Typical_angina', 'Atypical_angina','Asymptomatic'],
+            help="Select the type of chest pain",
+        )
+        chestpain = np.nan if chestpain == 'No Data Available' else chestpain
+        restingBP = st.number_input("Resting Blood Pressure", min_value = (-1), max_value=300, step=1, format="%d", help="Enter the resting blood pressure (in mmHg), '-1' corresponds to unknown resting blood pressure")
+        restingBP = np.nan if restingBP == (-1) else restingBP
+
+    with col2:
+        serum_cholesterol = st.number_input(
+            "Serum Cholesterol", min_value=(-1), max_value=1000, step=1, format="%d", help="Enter serum cholesterol level (in mg/dL), '-1' corresponds to unknown serum choesterol level"
+        )
+        serum_cholesterol = np.nan if serum_cholesterol == (-1) else serum_cholesterol
+        fasting_blood_sugar = st.radio(
+            "Fasting Blood Sugar > 120 mg/dL", ['Yes', 'No','No Data Available'], horizontal=True, help ="Indicate if fasting blood sugar is greater than 120 mg/dL"
+        )
+        fasting_blood_sugar = np.nan if fasting_blood_sugar == 'No Data Available' else fasting_blood_sugar
+        restingrelectro = st.selectbox(
+            "Resting Electrocardiographic Results",
+            ['No Data Available','ST-T_wave_abnormality', 'Normal', 'Left_ventricular_hypertrophy'],
+            help="Select the resting electrocardiographic result",
+        )
+        restingrelectro = np.nan if restingrelectro == 'No Data Available' else restingrelectro
+        maxheartrate = st.number_input(
+            "Maximum Heart Rate Achieved", min_value=(-1), max_value=250, step=1, format="%d", help="Enter the maximum heart rate achieved, '-1' corresponds to unknown maximum heart rate"
+        )
+        maxheartrate = np.nan if maxheartrate == (-1) else maxheartrate
+
+
+    # Second row of inputs
+    exerciseangia = st.radio("Exercise-Induced Angina", ['Yes', 'No','No Data Available'], horizontal=True)
+    exerciseangia = np.nan if exerciseangia == 'No Data Available' else exerciseangia
+    oldpeak = st.number_input("ST Depression Induced by Exercise", step = 0.1, help="Enter ST depression value induced by exercise relative to rest, any negetive value corresponds to unknown oldpeak value")
+    oldpeak = np.nan if oldpeak < 0 else oldpeak
+    slope = st.selectbox("Slope of Peak Exercise ST Segment", ['No Data Available','Downsloping', 'Upsloping', 'Flat'])
+    slope = np.nan if slope == 'No Data Available' else slope
+    noofmajorvessels = st.selectbox(
+        "Number of Major Vessels Colored by Fluoroscopy", ['No Data Available','Zero', 'One', 'Two', 'Three']
+    )
+    noofmajorvessels = np.nan if noofmajorvessels == 'No Data Available' else noofmajorvessels
+
+    # Submit button
+    submitted = st.form_submit_button("Predict")
+
+# Load model
+model_1 = pickle.load(open(r"C:\Users\user\Downloads\New folder\rfc.pkl", "rb"))
+
+# Prediction
+if submitted:
+    with st.spinner("Analyzing the data..."):
+        result = model_1.predict([[
+            age, gender, chestpain, restingBP, serum_cholesterol,
+            fasting_blood_sugar, restingrelectro, maxheartrate, exerciseangia,
+            oldpeak, slope, noofmajorvessels
+        ]])
+        
+    # Display result
+    st.markdown(
+        "### Prediction Result:", unsafe_allow_html=True
+    )
+
+    if result[0] == "Present":
+        st.info("The patient is likely to have heart disease. Please consult a doctor for further evaluation.")
+    else:
+        st.success("The patient is unlikely to have heart disease. However, maintaining regular check-ups is recommended.")
+
+# Footer
+st.markdown(
+    '''---\n
+    Developed by Abhisikta Moharana (https://www.linkedin.com/in/abhisikta-moharana-983052270)''',
+    unsafe_allow_html=True,
+)
+

requirements.txt

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+altair==5.5.0
+attrs==24.2.0
+blinker==1.9.0
+cachetools==5.5.0
+certifi==2024.8.30
+charset-normalizer==3.4.0
+click==8.1.7
+colorama==0.4.6
+gitdb==4.0.11
+GitPython==3.1.43
+idna==3.10
+Jinja2==3.1.4
+joblib==1.4.2
+jsonschema==4.23.0
+jsonschema-specifications==2024.10.1
+markdown-it-py==3.0.0
+MarkupSafe==3.0.2
+mdurl==0.1.2
+narwhals==1.17.0
+numpy==2.2.0
+packaging==24.2
+pandas==2.2.3
+pillow==11.0.0
+protobuf==5.29.1
+pyarrow==18.1.0
+pydeck==0.9.1
+Pygments==2.18.0
+python-dateutil==2.9.0.post0
+pytz==2024.2
+referencing==0.35.1
+requests==2.32.3
+rich==13.9.4
+rpds-py==0.22.3
+scikit-learn==1.4.2
+scipy==1.14.1
+six==1.17.0
+smmap==5.0.1
+streamlit==1.41.0
+tenacity==9.0.0
+threadpoolctl==3.5.0
+toml==0.10.2
+tornado==6.4.2
+typing_extensions==4.12.2
+tzdata==2024.2
+urllib3==2.2.3
+watchdog==6.0.0

rfc.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:e7d16756669b08d7cf1784bb0e41a549f95f2a35fe15124a66ba93bd1c757911
+size 6664693