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Update app.py
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app.py
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import streamlit as st
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import pandas as pd
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import
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import os
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# Function to load data from
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def load_data():
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df['Visit Date'] = pd.to_datetime(df['Visit Date'], errors='coerce')
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df['Age'] = df['Date of Birth'].apply(lambda dob: (dt.datetime.now() - dob).days // 365)
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return df
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# Function to save data to
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def save_data(df):
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# Load
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df = load_data()
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# Sidebar
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import streamlit as st
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import pandas as pd
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import json
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from datetime import datetime
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# Function to load patient data from JSON
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def load_data():
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with open('data.json', 'r') as f:
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return pd.DataFrame(json.load(f))
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# Function to save patient data to JSON
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def save_data(df):
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with open('data.json', 'w') as f:
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json.dump(df.to_dict(orient='records'), f, indent=4)
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# Load the existing data
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df = load_data()
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# Sidebar for navigation
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st.sidebar.title("Navigation")
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options = ["View Patient Data", "Add New Patient", "Add New Visit"]
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choice = st.sidebar.selectbox("Choose an option", options)
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if choice == "View Patient Data":
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# Sidebar for Patient Selection
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st.sidebar.header('Select Patient')
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patient_id = st.sidebar.selectbox('Patient ID', df['patient_id'].unique())
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# Filter Data for Selected Patient
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patient_data = df[df['patient_id'] == patient_id]
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# Display Patient Profile
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st.header('Patient Profile')
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st.write(f"Name: {patient_data['name'].values[0]}")
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st.write(f"Age: {patient_data['age'].values[0]}")
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st.write(f"Gender: {patient_data['gender'].values[0]}")
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st.write(f"Medical History: {patient_data['medical_history'].values[0]}")
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# Visualization of Vital Signs
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st.header('Vital Signs Over Time')
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# Line Chart for Heart Rate
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fig = px.line(patient_data, x='date', y='heart_rate', title='Heart Rate Over Time')
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st.plotly_chart(fig)
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# Line Chart for Blood Pressure
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fig = px.line(patient_data, x='date', y='blood_pressure', title='Blood Pressure Over Time')
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st.plotly_chart(fig)
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# Line Chart for Blood Glucose
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fig = px.line(patient_data, x='date', y='blood_glucose', title='Blood Glucose Over Time')
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st.plotly_chart(fig)
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# Dropdown for selecting specific visit details
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st.header('Previous Visit Details')
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selected_date = st.selectbox('Select Visit Date', patient_data['date'].unique())
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selected_visit = patient_data[patient_data['date'] == selected_date]
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st.write(f"**Visit Date:** {selected_date}")
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st.write(f"Heart Rate: {selected_visit['heart_rate'].values[0]}")
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st.write(f"Blood Pressure: {selected_visit['blood_pressure'].values[0]}")
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st.write(f"Blood Glucose: {selected_visit['blood_glucose'].values[0]}")
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# Alerts and Notifications
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st.header('Alerts')
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if selected_visit['heart_rate'].values[0] > 100:
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st.error('High heart rate detected!')
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if selected_visit['blood_pressure'].values[0] > 140:
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st.error('High blood pressure detected!')
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# Download Button for Patient Data
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st.download_button(
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label="Download Patient Data as CSV",
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data=patient_data.to_csv().encode('utf-8'),
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file_name=f'patient_{patient_id}_data.csv',
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mime='text/csv',
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)
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elif choice == "Add New Patient":
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st.header("Add New Patient")
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# Input fields for new patient data
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new_patient_id = st.number_input("Patient ID", min_value=0, step=1)
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new_name = st.text_input("Name")
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new_age = st.number_input("Age", min_value=0, step=1)
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new_gender = st.selectbox("Gender", ["Male", "Female"])
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new_medical_history = st.text_area("Medical History")
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if st.button("Add Patient"):
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new_patient_data = {
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'patient_id': new_patient_id,
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'name': new_name,
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'age': new_age,
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'gender': new_gender,
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'medical_history': new_medical_history,
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'date': None,
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'heart_rate': None,
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'blood_pressure': None,
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'blood_glucose': None,
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'temperature': None,
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'medical_complaints': None,
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'symptoms': None,
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'physical_examination': None,
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'diagnosis': None,
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'extra_notes': None,
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'treatment': None
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}
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df = pd.concat([df, pd.DataFrame([new_patient_data])], ignore_index=True)
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save_data(df)
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st.success("New patient added successfully!")
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elif choice == "Add New Visit":
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st.header("Add New Visit")
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# Input fields for adding a new visit
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patient_id = st.number_input("Patient ID", min_value=0, step=1)
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visit_date = st.date_input("Date of Visit", value=datetime.today())
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medical_complaints = st.text_area("Medical Complaints")
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symptoms = st.text_area("Symptoms")
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physical_examination = st.text_area("Physical Examination")
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diagnosis = st.text_area("Diagnosis")
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heart_rate = st.number_input("Heart Rate", min_value=0)
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blood_pressure = st.number_input("Blood Pressure", min_value=0)
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temperature = st.number_input("Temperature", min_value=0)
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glucose = st.number_input("Blood Glucose", min_value=0)
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extra_notes = st.text_area("Extra Notes")
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treatment = st.text_area("Treatment")
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if st.button("Add Visit"):
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new_visit_data = {
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'patient_id': patient_id,
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'name': df[df['patient_id'] == patient_id]['name'].values[0],
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'age': df[df['patient_id'] == patient_id]['age'].values[0],
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'gender': df[df['patient_id'] == patient_id]['gender'].values[0],
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'medical_history': df[df['patient_id'] == patient_id]['medical_history'].values[0],
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'date': visit_date.strftime('%Y-%m-%d'),
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'heart_rate': heart_rate,
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'blood_pressure': blood_pressure,
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'blood_glucose': glucose,
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'temperature': temperature,
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'medical_complaints': medical_complaints,
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'symptoms': symptoms,
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'physical_examination': physical_examination,
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'diagnosis': diagnosis,
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'extra_notes': extra_notes,
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'treatment': treatment
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}
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df = pd.concat([df, pd.DataFrame([new_visit_data])], ignore_index=True)
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save_data(df)
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st.success("New visit added successfully!")
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