finddrugs.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Parse out medications from discharge summaries in MIMIC "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import pandas as pd\n",
    "import psycopg2\n",
    "import getpass\n",
    "import re\n",
    "\n",
    "# Import the finddrugs module\n",
    "import finddrugs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Create a database connection\n",
    "user = 'postgres'\n",
    "host = 'localhost'\n",
    "dbname = 'mimic'\n",
    "schema = 'mimiciii'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Connect to the database\n",
    "con = psycopg2.connect(dbname=dbname, user=user, host=host, \n",
    "                       password=getpass.getpass(prompt='Password:'.format(user)))\n",
    "cur = con.cursor()\n",
    "cur.execute('SET search_path to {}'.format(schema))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Get the notes to be analysed\n",
    "# NOTE: we are limiting the query to 100 rows here\n",
    "query = \\\n",
    "\"\"\"\n",
    "SELECT n.row_id, n.subject_id, n.hadm_id, n.category, n.description, n.text\n",
    "FROM noteevents n\n",
    "WHERE n.category like 'Discharge summary'\n",
    "LIMIT 100;\n",
    "\"\"\"\n",
    "\n",
    "data = pd.read_sql_query(query,con)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Search the notes\n",
    "finddrugs.search(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ROW_ID</th>\n",
       "      <th>SUBJECT_ID</th>\n",
       "      <th>HADM_ID</th>\n",
       "      <th>HIST_FOUND</th>\n",
       "      <th>DEPRESSION</th>\n",
       "      <th>ADMIT_FOUND</th>\n",
       "      <th>DIS_FOUND</th>\n",
       "      <th>GEN_DEPRESS_MEDS_FOUND</th>\n",
       "      <th>GROUP</th>\n",
       "      <th>SSRI</th>\n",
       "      <th>MISC</th>\n",
       "      <th>citalopram</th>\n",
       "      <th>escitalopram</th>\n",
       "      <th>fluoxetine</th>\n",
       "      <th>fluvoxamine</th>\n",
       "      <th>paroxetine</th>\n",
       "      <th>sertraline</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>174</td>\n",
       "      <td>22532</td>\n",
       "      <td>167853</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>175</td>\n",
       "      <td>13702</td>\n",
       "      <td>107527</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>176</td>\n",
       "      <td>13702</td>\n",
       "      <td>167118</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>177</td>\n",
       "      <td>13702</td>\n",
       "      <td>196489</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>178</td>\n",
       "      <td>26880</td>\n",
       "      <td>135453</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ROW_ID  SUBJECT_ID  HADM_ID  HIST_FOUND  DEPRESSION  ADMIT_FOUND  \\\n",
       "0     174       22532   167853           0           0            0   \n",
       "1     175       13702   107527           1           0            1   \n",
       "2     176       13702   167118           1           1            1   \n",
       "3     177       13702   196489           1           1            1   \n",
       "4     178       26880   135453           1           0            1   \n",
       "\n",
       "   DIS_FOUND  GEN_DEPRESS_MEDS_FOUND  GROUP  SSRI  MISC  citalopram  \\\n",
       "0          0                       0      0     0     0           0   \n",
       "1          1                       0      3     1     0           0   \n",
       "2          1                       0      3     1     0           0   \n",
       "3          1                       0      3     1     0           0   \n",
       "4          1                       0      3     1     0           1   \n",
       "\n",
       "   escitalopram  fluoxetine  fluvoxamine  paroxetine  sertraline  \n",
       "0             0           0            0           0           0  \n",
       "1             1           0            0           0           0  \n",
       "2             1           0            0           0           0  \n",
       "3             1           0            0           0           0  \n",
       "4             0           0            0           0           0  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# load the output to a dataframe\n",
    "medications = pd.read_csv('output.csv')\n",
    "medications.head()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}