app.py

import time
import re
import pandas as pd
import numpy as np
import torch
import torch.nn.functional as F
import graphviz as graphviz
import pydeck as pdk
import streamlit as st

from transformers import AutoTokenizer, AutoModel
from tokenizers import Tokenizer, AddedToken
from st_click_detector import click_detector

st.set_page_config(page_title="OMS Omaha System and LOCUS MH Ontology Models",layout='wide')


st.write("Circulation Categorization")

st.graphviz_chart('''digraph {
29CIRCULATION -> AbnormalBloodPressureReading
29CIRCULATION -> AbnormalCardiacLaboratoryResults
29CIRCULATION -> AbnormalClotting
29CIRCULATION -> AbnormalHeartSoundsMurmurs
29CIRCULATION -> AnginalPain
29CIRCULATION -> CrampingPainofExtremities
29CIRCULATION -> DecreasedPulses
29CIRCULATION -> DiscolorationofSkinCyanosis
29CIRCULATION -> EdemaSwellinginlegsarmsfeet
29CIRCULATION -> ExcessivelyRapidHeartRate
29CIRCULATION -> IrregularHeartRate
29CIRCULATION -> SyncopalEpisodesFaintingDizziness
29CIRCULATION -> TemperatureChangeinAffectedArea
29CIRCULATION -> Varicosities
}''')