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import pandas as pd
import streamlit as st
from utils_casemaker import CaseMaker, format_casemaker_data
st.title("Juni Health Patient Casemaker")
casemaker = CaseMaker("terms.json")
uploaded_file = st.file_uploader("Choose a file")
if uploaded_file is not None:
# Can be used wherever a "file-like" object is accepted:
df = pd.read_csv(uploaded_file)
reports = format_casemaker_data(
df=df,
patient_id_column="patient_id",
date_column="report_id",
text_column="text",
)
patient_options = {
f"Patient {patient_id}: {len(reports[patient_id])} reports": patient_id
for patient_id in reports.keys()
}
selected_patient_string = st.radio(
"Select a Patient ID",
list(patient_options.keys()),
key = "patient_select_button"
)
if st.button("Generate Case", key = "task_begin_button"):
selected_patient_id = patient_options[selected_patient_string]
summary_by_organ = casemaker.parse_records(reports[selected_patient_id])
summary_by_organ = casemaker.format_reports(summary_by_organ)
for chosen_organ in summary_by_organ.keys():
if summary_by_organ[chosen_organ]:
st.header(chosen_organ.capitalize())
st.write(summary_by_organ[chosen_organ]) |