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  ->  SyncopalEpisodes(Fainting)Dizziness
        29CIRCULATION  ->  TemperatureChangeinAffectedArea
        29CIRCULATION  ->  Varicosities
        }
''')