mimic-citations.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# 1. PubMed\n",
    "\n",
    "Search PubMed for papers\n",
    "\n",
    "https://www.ncbi.nlm.nih.gov/pubmed/\n",
    "\n",
    "https://www.ncbi.nlm.nih.gov/books/NBK25499/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "from collections import Counter\n",
    "import datetime\n",
    "import os\n",
    "\n",
    "import lcp.reuse as reuse\n",
    "from Bio import Entrez\n",
    "from IPython.display import display\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Define folders"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "SEARCH_RESULT_FOLDER = 'search_results'\n",
    "MIMIC_PUBMED_CITATION_FOLDER = 'MIMIC_Pubmed_Citations'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Define search queries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "MIMIC_QUERY = '(mimic-ii OR mimic-iii OR mimic-iv OR mimicii OR mimiciii OR mimiciv OR mimic-2 OR mimic-3 OR mimic-4 OR mimic2 OR mimic3 OR mimic4)'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "PROJECT = 'MIMIC' #'eICU'\n",
    "\n",
    "def full_query(base_query, restriction_query):\n",
    "    return ' AND '.join([base_query, restriction_query])\n",
    "\n",
    "entrez_email = 'mimic-support@physionet.org'\n",
    "if PROJECT == 'MIMIC':\n",
    "    PMID = None\n",
    "elif PROJECT == 'eICU':\n",
    "    # Retrieves publications which cite this reference\n",
    "    PMID = '30204154'\n",
    "\n",
    "if PROJECT == 'MIMIC':\n",
    "    base_query = MIMIC_QUERY\n",
    "elif PROJECT == 'eICU':\n",
    "    base_query = f'(eicu-crd OR \"eICU Collaborative Research Database\" OR (eicu AND ({MIMIC_QUERY} OR database OR MIT OR Phillips)))'\n",
    "# Other terms added to remove false positives. The more terms added without increasing FPs, the better.\n",
    "if PROJECT == 'MIMIC':\n",
    "    restriction_query = '(physionet OR icu OR \"intensive care\" OR \"critical care\")'\n",
    "elif PROJECT == 'eICU':\n",
    "    restriction_query = '(\"intensive care\" OR \"critical care\")'\n",
    "# more restriction keyword ideas: clinical, database, waveform (not suitable on their own due to general mimic term)\n",
    "full_query = full_query(base_query, restriction_query)\n",
    "\n",
    "if PMID:\n",
    "    search_strings = [\n",
    "        'PMID'\n",
    "    ]\n",
    "else:\n",
    "    search_strings = [\n",
    "        #base_query#,\n",
    "        full_query\n",
    "    ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# search_results = reuse.search_list(search_strings, entrez_email)\n",
    "if PMID:\n",
    "    citations = []\n",
    "    pmc_ids = Entrez.read(Entrez.elink(dbfrom='pubmed', db='pmc', LinkName='pubmed_pmc_refs', from_uid=PMID))\n",
    "    pmc_ids = [list(i.values())[0] for i in pmc_ids[0]['LinkSetDb'][0]['Link']]\n",
    "    pm_ids = Entrez.read(Entrez.elink(dbfrom='pmc', db='pubmed', LinkName='pmc_pubmed', from_uid=','.join(pmc_ids)))\n",
    "    for pm_id in [list(i.values())[0] for i in pm_ids[0]['LinkSetDb'][0]['Link']]:\n",
    "        citations.append(pm_id)\n",
    "    search_results_all = reuse.search_list(entrez_email, ids=citations, all=True)\n",
    "else:\n",
    "    search_results_all = reuse.search_list(entrez_email, search_strings=search_strings, all=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Display number of results\n",
    "if PMID:\n",
    "    result = search_results_all['PMID']\n",
    "    print(f'PMID:\\n - Count: {len(result.index)}')\n",
    "else:\n",
    "    for ss in search_strings:\n",
    "        result = search_results_all[ss]\n",
    "        print(f'{ss}:\\n - Count: {len(result.index)}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Write the titles to files\n",
    "write_dir = os.path.join(SEARCH_RESULT_FOLDER, PROJECT, 'pubmed')\n",
    "os.makedirs(write_dir, exist_ok=True)\n",
    "\n",
    "if PMID:\n",
    "    search_results_all['PMID'].to_csv(os.path.join(write_dir, 'PMID-citations-all.csv'), index=False)\n",
    "else:\n",
    "    search_results_all[base_query].to_csv(os.path.join(write_dir, 'without-constraints-all.csv'), index=False)\n",
    "    search_results_all[full_query].to_csv(os.path.join(write_dir, 'with-constraints-all.csv'), index=False)\n",
    "\n",
    "# base_query_file = os.path.join(write_dir, 'without-constraints.txt')\n",
    "# with open(base_query_file, 'w') as f:\n",
    "#     for line in search_results[base_query].paper_titles:\n",
    "#         f.write(line+'\\n')\n",
    "\n",
    "# full_query_file = os.path.join(write_dir, 'with-constraints.txt')\n",
    "# with open(full_query_file, 'w') as f:\n",
    "#     for line in search_results[full_query].paper_titles:\n",
    "#         f.write(line+'\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a new one for each year\n",
    "if PMID:\n",
    "    all_years = sorted(set(list(search_results_all['PMID']['Publication Year'])))\n",
    "    for year in all_years:\n",
    "        year_df = search_results_all['PMID'][search_results_all['PMID']['Publication Year'] == year]\n",
    "        year_df.to_csv(os.path.join(write_dir, f'PMID-citations-all_{year}.csv'), index=False)\n",
    "else:\n",
    "    all_years = sorted(set(list(search_results_all[full_query]['Publication Year'])))\n",
    "    for year in all_years:\n",
    "        year_df_without = search_results_all[base_query][search_results_all[base_query]['Publication Year'] == year]\n",
    "        year_df_with = search_results_all[full_query][search_results_all[full_query]['Publication Year'] == year]\n",
    "        year_df_without.to_csv(os.path.join(write_dir, f'without-constraints-all_{year}.csv'), index=False)\n",
    "        year_df_with.to_csv(os.path.join(write_dir, f'with-constraints-all_{year}.csv'), index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a histogram of number of publications each year\n",
    "if PMID:\n",
    "    all_years = sorted(set(list(search_results_all['PMID']['Publication Year'])))\n",
    "\n",
    "    years = []\n",
    "    for year in all_years:\n",
    "        year_df = search_results_all['PMID'][search_results_all['PMID']['Publication Year'] == year]\n",
    "\n",
    "        for _ in range(len(year_df.index)):\n",
    "            years.append(year)\n",
    "\n",
    "    plt.figure(figsize=(10,6))\n",
    "    plt.hist(years, facecolor='k', edgecolor='w', bins=np.arange(len(all_years)+1)-0.5)\n",
    "    plt.savefig(os.path.join(write_dir, 'PMID-citations_histogram.jpg'))\n",
    "    plt.xlabel('Year', fontsize=12)\n",
    "    plt.ylabel('Number of Publications', fontsize=12)\n",
    "    plt.show()\n",
    "else:\n",
    "    all_years = sorted(set(list(search_results_all[full_query]['Publication Year'])))\n",
    "\n",
    "    year_without = []\n",
    "    year_with = []\n",
    "    for year in all_years:\n",
    "        year_df_without = search_results_all[base_query][search_results_all[base_query]['Publication Year'] == year]\n",
    "        year_df_with = search_results_all[full_query][search_results_all[full_query]['Publication Year'] == year]\n",
    "\n",
    "        for _ in range(len(year_df_without.index)):\n",
    "            year_without.append(year)\n",
    "        for _ in range(len(year_df_with.index)):\n",
    "            year_with.append(year)\n",
    "\n",
    "    plt.figure(figsize=(10,6))\n",
    "    plt.hist(year_without, facecolor='k', edgecolor='w', bins=np.arange(len(all_years)+1)-0.5)\n",
    "    plt.savefig(os.path.join(write_dir, 'without-constraints_histogram.jpg'))\n",
    "    plt.xlabel('Year', fontsize=12)\n",
    "    plt.ylabel('Number of Publications', fontsize=12)\n",
    "    plt.show()\n",
    "\n",
    "    plt.figure(figsize=(10,6))\n",
    "    plt.hist(year_with, facecolor='k', edgecolor='w', bins=np.arange(len(all_years)+1)-0.5)\n",
    "    plt.savefig(os.path.join(write_dir, 'with-constraints_histogram.jpg'))\n",
    "    plt.xlabel('Year', fontsize=12)\n",
    "    plt.ylabel('Number of Publications', fontsize=12)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# DO: Create a file called without-constraints-inspected.tsv and mark the second column with T/F for true/false positives.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Look at the effect of restricting the search by additional criteria.\n",
    "# The differences show that many false positives, and a few true positives, are removed.\n",
    "reuse.showdiff(search_results[search_strings[0]],\n",
    "               search_results[search_strings[1]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Read in the labelled results for the general unconstrained search query\n",
    "labelled_results = pd.read_csv(os.path.join(write_dir, 'without-constraints-inspected.tsv'), delimiter='\\t', header=None)\n",
    "false_positives = labelled_results.loc[labelled_results[1]=='F'][0].values\n",
    "true_positives = labelled_results.loc[labelled_results[1]=='T'][0].values\n",
    "print('Number of results found using the unconstrained search term:', len(labelled_results))\n",
    "print('Number of false positives:',len(false_positives))\n",
    "print('Number of true positives:',len(true_positives))\n",
    "\n",
    "constrained_titles = search_results[search_strings[1]].paper_titles\n",
    "print('\\nCompare ^ true positives with:')\n",
    "print('Number of results from the constrained search term:', len(constrained_titles))\n",
    "\n",
    "missed_papers = set(true_positives) - set(constrained_titles)\n",
    "print('Number of missed true positives:', len(missed_papers))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Take a look at some True positives missed by the constrained search term to figure out what else you can add.\n",
    "# Write to a file to label comments.\n",
    "write_dir = os.path.join(SEARCH_RESULT_FOLDER, 'pubmed')\n",
    "\n",
    "missed_papers_file = os.path.join(write_dir, 'missed-papers.tsv')\n",
    "\n",
    "with open(missed_papers_file, 'w') as f:\n",
    "    for line in missed_papers:\n",
    "        f.write(line+'\\n')\n",
    "\n",
    "display(missed_papers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2. Web of Science"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from selenium import webdriver\n",
    "from selenium.webdriver.common.keys import Keys\n",
    "import re\n",
    "import time\n",
    "from IPython.display import display\n",
    "\n",
    "\n",
    "restriction_query = '(physionet OR icu OR “intensive care” OR “critical care”)'\n",
    "def full_query(base_query, restriction_query):\n",
    "    return ' AND '.join([base_query, restriction_query])\n",
    "full_mimic_query = full_query(MIMIC_QUERY, restriction_query)\n",
    "#base_search_url = 'https://apps.webofknowledge.com/WOS_GeneralSearch_input.do?product=WOS&search_mode=GeneralSearch&SID=2F46AeWkMQBRAZlzDWm&preferencesSaved='\n",
    "base_search_url = 'https://apps.webofknowledge.com/WOS_GeneralSearch_input.do?product=WOS&search_mode=GeneralSearch&SID=1AnC2UMojuKrtrl7T5R&preferencesSaved='\n",
    "\n",
    "all_titles = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get to the search page\n",
    "driver = webdriver.Firefox()\n",
    "driver.get(base_search_url)\n",
    "\n",
    "# Input the query string\n",
    "time.sleep(2.5)\n",
    "searchbox = driver.find_element_by_id('value(input1)')\n",
    "searchbox.send_keys(full_mimic_query)\n",
    "\n",
    "# Search\n",
    "time.sleep(1)\n",
    "searchbutton = driver.find_element_by_css_selector('.standard-button.primary-button.large-search-button')\n",
    "searchbutton.click()\n",
    "\n",
    "# Get the total number of pages\n",
    "npages = int(driver.find_element_by_id('pageCount.top').text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get the titles!!!\n",
    "while True:\n",
    "    # Get the current page number\n",
    "    pagenum = int(driver.find_element_by_class_name('goToPageNumber-input').get_property('value'))\n",
    "\n",
    "    # Get the titles. This also captures the journals. So every second value is not a title.\n",
    "    elements = driver.find_elements_by_class_name('smallV110')\n",
    "\n",
    "    for e in elements[::2]:\n",
    "        all_titles.append(e.find_element_by_tag_name('value').text)\n",
    "        \n",
    "    if pagenum < npages:\n",
    "        nextbutton = driver.find_element_by_class_name('paginationNext')\n",
    "        nextbutton.click()\n",
    "    else:\n",
    "        print('Got all paper titles!')\n",
    "        driver.close()\n",
    "        break\n",
    "        \n",
    "all_titles = set(all_titles)\n",
    "#all_titles.remove('')\n",
    "all_titles = [t.lower() for t in list(all_titles)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "display(all_titles)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Write the titles to files\n",
    "write_dir = os.path.join('search_results/wos')\n",
    "\n",
    "full_query_file = os.path.join(write_dir, 'with-constraints.txt')\n",
    "\n",
    "with open(full_query_file, 'w') as f:\n",
    "    for line in all_titles:\n",
    "        f.write(line+'\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3. SCOPUS\n",
    "\n",
    "Shit search"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 4. IEEE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from selenium import webdriver\n",
    "from selenium.webdriver.common.keys import Keys\n",
    "import re\n",
    "import time\n",
    "from IPython.display import display\n",
    "import os\n",
    "\n",
    "restriction_query = '(physionet OR icu OR “intensive care” OR “critical care”)'\n",
    "def full_query(base_query, restriction_query):\n",
    "    return ' AND '.join([base_query, restriction_query])\n",
    "full_mimic_query = full_query(MIMIC_QUERY, restriction_query)\n",
    "base_search_url = 'http://ieeexplore.ieee.org/search/advsearch.jsp?expression-builder'\n",
    "all_titles = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get to the search page\n",
    "driver = webdriver.Firefox()\n",
    "driver.get(base_search_url)\n",
    "\n",
    "# Input the query string\n",
    "searchbox = driver.find_element_by_id('expression-textarea')\n",
    "searchbox.send_keys(full_mimic_query)\n",
    "# Select the 'full text and metadata' box\n",
    "radiobutton = driver.find_element_by_id('Search_All_Text')\n",
    "radiobutton.click()\n",
    "\n",
    "# Search\n",
    "time.sleep(1)\n",
    "searchbutton = driver.find_element_by_class_name('stats-Adv_Command_search')\n",
    "searchbutton.click()\n",
    "\n",
    "# Get the total number of pages\n",
    "#npages = int(driver.find_element_by_id('pageCount.top').text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get the titles!!!\n",
    "while True:\n",
    "    # let the page load\n",
    "    time.sleep(2)\n",
    "    # Get scroll height\n",
    "    last_height = driver.execute_script(\"return document.body.scrollHeight\")\n",
    "    while True:\n",
    "        driver.execute_script(\"window.scrollTo(0, document.body.scrollHeight);\")\n",
    "        time.sleep(0.5)\n",
    "        new_height = driver.execute_script(\"return document.body.scrollHeight\")\n",
    "        if new_height == last_height:\n",
    "            break\n",
    "        last_height = new_height\n",
    "        \n",
    "    # Get the titles.\n",
    "    # They are in: <h2 class=\"result-item-title\"><a class=\"ng-binding ng-scope\">title</a></h2>\n",
    "    elements = driver.find_elements_by_class_name('result-item-title')\n",
    "    for e in elements:\n",
    "        # Text may appear with \"[::sometext::]\"\n",
    "        all_titles.append(e.find_element_by_tag_name('a').get_attribute('text').replace('[::', '').replace('::]', ''))\n",
    "        # New line separated journal info and such\n",
    "        #all_titles.append(e.text.split('\\n')[0])\n",
    "    \n",
    "    # Click next page if any\n",
    "    \n",
    "    e = driver.find_element_by_class_name('next')\n",
    "    if 'disabled' in e.get_attribute('class'):\n",
    "        print('Got all paper titles!')\n",
    "        driver.close()\n",
    "        break\n",
    "    else:\n",
    "        nextbutton = driver.find_element_by_link_text('>')\n",
    "        nextbutton.click()\n",
    "\n",
    "all_titles = set(all_titles)\n",
    "all_titles = [t.lower() for t in list(all_titles)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(len(all_titles))\n",
    "display(all_titles)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Write the titles to files\n",
    "write_dir = os.path.join('search_results/ieee')\n",
    "\n",
    "full_query_file = os.path.join(write_dir, 'with-constraints.txt')\n",
    "\n",
    "with open(full_query_file, 'w') as f:\n",
    "    for line in all_titles:\n",
    "        f.write(line+'\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Combining Results - pubmed, wos, ieee"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "result_dir = SEARCH_RESULT_FOLDER\n",
    "\n",
    "combined_results = []\n",
    "for service in ['pubmed', 'wos', 'ieee']:\n",
    "    # For pubmed, get the curated true positives from the unconstrained search instead\n",
    "    if service == 'pubmed':\n",
    "        df = pd.read_csv(os.path.join(result_dir, service, 'without-constraints-inspected.tsv'), delimiter='\\t', header=None)\n",
    "        service_results = list(df.loc[df[1]=='T'][0].values)\n",
    "    # For other services, get the constrained search results\n",
    "    else:\n",
    "        with open(os.path.join(result_dir, service, 'with-constraints.txt')) as f:\n",
    "            service_results = f.readlines()\n",
    "    print('Number of results from service '+service+': '+str(len(service_results)))\n",
    "    combined_results = combined_results + [r.strip() for r in service_results]\n",
    "\n",
    "print('\\nTotal number of non-unique results: ', len(combined_results))\n",
    "combined_results = sorted(list(set(combined_results)))\n",
    "print('Total number of unique results: ', len(combined_results))\n",
    "with open(os.path.join(result_dir, 'combined', 'with-constraints.txt'), 'w') as f:\n",
    "    for r in combined_results:\n",
    "        f.write(r+'\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# may 21 2018\n",
    "Number of results from service pubmed: 155\n",
    "Number of results from service wos: 152\n",
    "Number of results from service ieee: 322\n",
    "\n",
    "Total number of non-unique results:  629\n",
    "Total number of unique results:  456\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Attempting to parse GS automatically failed. Below is evidence of failure. Can ignore..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# N. Search Google Scholar\n",
    "\n",
    "Packages found online:\n",
    "- https://github.com/ckreibich/scholar.py\n",
    "- https://github.com/venthur/gscholar\n",
    "- https://github.com/adeel/google-scholar-scraper\n",
    "- http://code.activestate.com/recipes/523047-search-google-scholar/\n",
    "- https://github.com/erdiaker/torrequest\n",
    "- https://github.com/NikolaiT/GoogleScraper\n",
    "\n",
    "\n",
    "- https://stackoverflow.com/questions/8049520/web-scraping-javascript-page-with-python\n",
    "\n",
    "\n",
    "Query: `(\"mimic ii\" OR \"mimic iii\") AND (\"database\" OR \"clinical\" OR \"waveform\" OR ICU)`\n",
    "\n",
    "https://scholar.google.com/scholar?q=%28mimic-ii+OR+mimic-iii%29&btnG=&hl=en&as_sdt=1%2C22&as_vis=1\n",
    "\n",
    "https://scholar.google.com/scholar/help.html\n",
    "\n",
    "\n",
    "https://superuser.com/questions/565722/how-to-config-tor-to-use-a-http-socks-proxy\n",
    "\n",
    "## Requirements\n",
    "\n",
    "1. Browse with JS enabled. requests library uses http. Otherwise google will think (correctly) that you are a robot.\n",
    "2. Change IP every time, or google will block."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scholarly import scholarly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "PROJECT = 'eICU'\n",
    "\n",
    "# Search by Google Scholar publication ID\n",
    "search_results = []\n",
    "if PROJECT == 'eICU':\n",
    "    try:\n",
    "        search_results.append(scholarly.search_citedby(11878669525996073977))\n",
    "    except Exception as e:\n",
    "        print(e)\n",
    "\n",
    "total_results = search_results[0].total_results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# all_pubs = list(search_results)\n",
    "all_pubs = []\n",
    "for i in range(total_results):\n",
    "    print(100*i/total_results)\n",
    "    try:\n",
    "        ct = next(search_results)\n",
    "        all_pubs.append({\n",
    "            'title': ct['bib']['title'],\n",
    "            'pub_year': ct['bib']['pub_year']\n",
    "        })\n",
    "    except:\n",
    "        pass\n",
    "# print(all_pubs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Manually get the number of citations from Google Scholar\n",
    "## Methods:\n",
    "### 1. Go to: https://scholar.google.com/\n",
    "### 2. Type a query to get a specific MIMIC DB, i.e., \"`mimic-iv`\" for MIMIC-IV\n",
    "### 3. Find the original paper (usually the first result, or top cited one)\n",
    "### 4. Click on \"`Cited by ###`\" underneath the brief abstract\n",
    "### 5. On the left side, click \"`Custom range...`\"\n",
    "### 6. In both boxes, type the year you want to query, i.e., \"`2023 - 2023`\" to return results for only 2023, click \"`Search`\"\n",
    "### 7. At the top, under the search bar is the number of citations that year (note, the \"`About ### results`\" is the exact number of results until around 1000 or so when it rounds to the nearest 20 I think due to the massive pagination request but still close enough at those numbers)\n",
    "\n",
    "----\n",
    "### TODO: automate this!!! but I know GS will get mad at me for all those requests ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "google_scholar_mimic_pubs = {\n",
    "    'mimic-i': {\n",
    "        '1997' :   2,\n",
    "        '1998' :   1,\n",
    "        '1999' :   2,\n",
    "        '2000' :   4,\n",
    "        '2001' :   4,\n",
    "        '2002' :   4,\n",
    "        '2003' :   3,\n",
    "        '2004' :   7,\n",
    "        '2005' :   5,\n",
    "        '2006' :  10,\n",
    "        '2007' :  12,\n",
    "        '2008' :   3,\n",
    "        '2009' :   9,\n",
    "        '2010' :  10,\n",
    "        '2011' :  12,\n",
    "        '2012' :   7,\n",
    "        '2013' :   9,\n",
    "        '2014' :   7,\n",
    "        '2015' :  13,\n",
    "        '2016' :  18,\n",
    "        '2017' :  25,\n",
    "        '2018' :  14,\n",
    "        '2019' :  17,\n",
    "        '2020' :  30,\n",
    "        '2021' :  29,\n",
    "        '2022' :  23,\n",
    "        '2023' :  19,\n",
    "        '2024' :   0\n",
    "    },\n",
    "    'mimic-ii': {\n",
    "        '1997' :    0,\n",
    "        '1998' :    0,\n",
    "        '1999' :    0,\n",
    "        '2000' :    0,\n",
    "        '2001' :    0,\n",
    "        '2002' :    0,\n",
    "        '2003' :    0,\n",
    "        '2004' :    0,\n",
    "        '2005' :    0,\n",
    "        '2006' :    0,\n",
    "        '2007' :    0,\n",
    "        '2008' :    0,\n",
    "        '2009' :    0,\n",
    "        '2010' :    0,\n",
    "        '2011' :   11,\n",
    "        '2012' :   37,\n",
    "        '2013' :   53,\n",
    "        '2014' :   81,\n",
    "        '2015' :  126,\n",
    "        '2016' :  175,\n",
    "        '2017' :  116,\n",
    "        '2018' :  122,\n",
    "        '2019' :  115,\n",
    "        '2020' :  118,\n",
    "        '2021' :  101,\n",
    "        '2022' :  112,\n",
    "        '2023' :   91,\n",
    "        '2024' :    0\n",
    "    },\n",
    "    'mimic-iii': {\n",
    "        '1997' :    0,\n",
    "        '1998' :    0,\n",
    "        '1999' :    0,\n",
    "        '2000' :    0,\n",
    "        '2001' :    0,\n",
    "        '2002' :    0,\n",
    "        '2003' :    0,\n",
    "        '2004' :    0,\n",
    "        '2005' :    0,\n",
    "        '2006' :    0,\n",
    "        '2007' :    0,\n",
    "        '2008' :    0,\n",
    "        '2009' :    0,\n",
    "        '2010' :    0,\n",
    "        '2011' :    0,\n",
    "        '2012' :    0,\n",
    "        '2013' :    0,\n",
    "        '2014' :    1,\n",
    "        '2014' :    0,\n",
    "        '2015' :    0,\n",
    "        '2016' :   24,\n",
    "        '2017' :  147,\n",
    "        '2018' :  428,\n",
    "        '2019' :  650,\n",
    "        '2020' :  960,\n",
    "        '2021' : 1260,\n",
    "        '2022' : 1440,\n",
    "        '2023' : 1280,\n",
    "        '2024' :    7\n",
    "    },\n",
    "    'mimic-iv': {\n",
    "        '1997' :   0,\n",
    "        '1998' :   0,\n",
    "        '1999' :   0,\n",
    "        '2000' :   0,\n",
    "        '2001' :   0,\n",
    "        '2002' :   0,\n",
    "        '2003' :   0,\n",
    "        '2004' :   0,\n",
    "        '2005' :   0,\n",
    "        '2006' :   0,\n",
    "        '2007' :   0,\n",
    "        '2008' :   0,\n",
    "        '2009' :   0,\n",
    "        '2010' :   0,\n",
    "        '2011' :   0,\n",
    "        '2012' :   0,\n",
    "        '2013' :   0,\n",
    "        '2014' :   0,\n",
    "        '2014' :   0,\n",
    "        '2015' :   0,\n",
    "        '2016' :   0,\n",
    "        '2017' :   0,\n",
    "        '2018' :   0,\n",
    "        '2019' :   0,\n",
    "        '2020' :   5,\n",
    "        '2021' :  57,\n",
    "        '2022' : 215,\n",
    "        '2023' : 272,\n",
    "        '2024' :   0\n",
    "    },\n",
    "    'mimic-cxr': {\n",
    "        '1997' :   0,\n",
    "        '1998' :   0,\n",
    "        '1999' :   0,\n",
    "        '2000' :   0,\n",
    "        '2001' :   0,\n",
    "        '2002' :   0,\n",
    "        '2003' :   0,\n",
    "        '2004' :   0,\n",
    "        '2005' :   0,\n",
    "        '2006' :   0,\n",
    "        '2007' :   0,\n",
    "        '2008' :   0,\n",
    "        '2009' :   0,\n",
    "        '2010' :   0,\n",
    "        '2011' :   0,\n",
    "        '2012' :   0,\n",
    "        '2013' :   0,\n",
    "        '2014' :   0,\n",
    "        '2014' :   0,\n",
    "        '2015' :   0,\n",
    "        '2016' :   0,\n",
    "        '2017' :   0,\n",
    "        '2018' :   0,\n",
    "        '2019' :   0,\n",
    "        '2020' :  24,\n",
    "        '2021' :  92,\n",
    "        '2022' : 181,\n",
    "        '2023' : 287,\n",
    "        '2024' :   0\n",
    "    }\n",
    "}\n",
    "\n",
    "closed_datasets = {\n",
    "    'UK Biobank': {\n",
    "        '2015':   18,\n",
    "        '2016':   95,\n",
    "        '2017':  232,\n",
    "        '2018':  468,\n",
    "        '2019':  697,\n",
    "        '2020':  891,\n",
    "        '2021': 1260,\n",
    "        '2022': 1650,\n",
    "        '2023': 1820,\n",
    "        '2024':   11\n",
    "    },\n",
    "    # 'CheXpert': {\n",
    "    #     '2017':   1,\n",
    "    #     '2018':   3,\n",
    "    #     '2019':  64,\n",
    "    #     '2020': 239,\n",
    "    #     '2021': 449,\n",
    "    #     '2022': 599,\n",
    "    #     '2023': 573,\n",
    "    #     '2024':  12\n",
    "    # },\n",
    "    'OpenSAFELY': {\n",
    "        '2019':   1,\n",
    "        '2020': 288,\n",
    "        '2021': 213,\n",
    "        '2022':  92,\n",
    "        '2023':  29,\n",
    "        '2024':   0\n",
    "    },\n",
    "    'All of Us': {\n",
    "        '2018':   1,\n",
    "        '2019':  13,\n",
    "        '2020':  92,\n",
    "        '2021': 175,\n",
    "        '2022': 223,\n",
    "        '2023': 303,\n",
    "        '2024':   2\n",
    "    }\n",
    "}\n",
    "\n",
    "total_funding = {\n",
    "    'MIMIC': 8253202,\n",
    "    'UK Biobank': 522.1e6,\n",
    "    # Welcome Trust (222097), MRC (MR/W016729/1), MRC (MR/V015757/1)?, MC_PC_20051, MC_PC_20058,\n",
    "    # MC_PC_20059, NIHR135559, COV-LT-0009, COV-LT2-0073\n",
    "    'OpenSAFELY': 2874941.71 + 774508.54 + 0 + 6055626.76 + 19188252.00 + 11454881.49 + 403228.32 + 12109587.17 + 854028.70,\n",
    "    'All of Us': 1.5e9,\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Graph the results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\lbmccullum\\OneDrive - Inside MD Anderson\\Documents\\citation-tracker\\env\\lib\\site-packages\\ipykernel_launcher.py:17: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray.\n",
      "  app.launch_new_instance()\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "colors = [\n",
    "    'cornflowerblue',\n",
    "    'lightsteelblue',\n",
    "    'dimgray',\n",
    "    'lightcoral',\n",
    "    'firebrick'\n",
    "]\n",
    "min_year = 2005\n",
    "ytick_interval = 1000\n",
    "\n",
    "years = [int(y) for y in google_scholar_mimic_pubs[list(google_scholar_mimic_pubs.keys())[0]].keys()]\n",
    "db_order = ['mimic-i','mimic-ii','mimic-iii','mimic-iv','mimic-cxr']\n",
    "\n",
    "plt.figure(figsize=(8,6))\n",
    "graph_data = []\n",
    "for db in google_scholar_mimic_pubs.keys():\n",
    "    graph_data.append(np.concatenate(np.array([np.array(v*[int(y)]) for y,v in google_scholar_mimic_pubs[db].items()]).flatten()))\n",
    "max_citations = np.concatenate(graph_data).shape[0]\n",
    "\n",
    "plt.hist(graph_data, len(graph_data[0]), color=colors, label=[s.upper() for s in db_order], cumulative=1, stacked=True, density=False, zorder=3)\n",
    "plt.xlim([min_year, max(years)-0.08])\n",
    "plt.xticks(rotation=-45)\n",
    "ax = plt.gca()\n",
    "ax.tick_params(axis='both', which='major', labelsize=12)\n",
    "ax.tick_params(axis='both', which='minor', labelsize=10)\n",
    "ax.set_xticks(np.arange(min_year, max(years), 1) + 0.5)\n",
    "ax.set_xticklabels(np.arange(min_year, max(years), 1), fontsize=12)\n",
    "ax.set_yticks(np.arange(0, max_citations+ytick_interval, ytick_interval))\n",
    "ax.set_yticklabels(np.arange(0, max_citations+ytick_interval, ytick_interval), fontsize=12)\n",
    "plt.xlabel('Publication Year', fontsize=14)\n",
    "plt.ylabel('Total Number of Publications', fontsize=14)\n",
    "handles, labels = plt.gca().get_legend_handles_labels()\n",
    "order = np.arange(len(db_order)-1, -1, -1)\n",
    "legend = plt.legend([handles[i] for i in order], [labels[i] for i in order], loc='upper left', fontsize=12)\n",
    "legend.get_frame().set_alpha(1)\n",
    "plt.grid(zorder=-1, axis='y')\n",
    "plt.tight_layout()\n",
    "plt.savefig(os.path.join(SEARCH_RESULT_FOLDER, 'google_scholar', 'cumulative_histogram.png'))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plot the growth of each DB adjusted from the start time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "colors = [\n",
    "    'cornflowerblue',\n",
    "    'lightsteelblue',\n",
    "    'dimgray',\n",
    "    'lightcoral',\n",
    "    'firebrick'\n",
    "]\n",
    "max_year = 2022\n",
    "ALL_MIMIC = True\n",
    "\n",
    "years = [int(y) for y in google_scholar_mimic_pubs[list(google_scholar_mimic_pubs.keys())[0]].keys()]\n",
    "db_order = ['mimic-i','mimic-ii','mimic-iii','mimic-iv','mimic-cxr']\n",
    "\n",
    "plt.figure(figsize=(8,6))\n",
    "\n",
    "if ALL_MIMIC:\n",
    "    all_x_data = []\n",
    "    all_y_data = []\n",
    "for i,db in enumerate(db_order):\n",
    "    for y,v in google_scholar_mimic_pubs[db].items():\n",
    "        if v != 0:\n",
    "            start_year = int(y)\n",
    "            break\n",
    "    y_data = [v for y,v in google_scholar_mimic_pubs[db].items() if ((int(y) >= start_year) and (int(y) <= max_year))]\n",
    "    y_data = np.cumsum(y_data)\n",
    "    if ALL_MIMIC:\n",
    "        all_y_data.append(y_data)\n",
    "    else:\n",
    "        x_data = range(len(y_data))\n",
    "        plt.plot(x_data, y_data, color=colors[i], label=db.upper())\n",
    "if ALL_MIMIC:\n",
    "    max_len = max([len(a) for a in all_y_data])\n",
    "    all_x_data = range(max_len)\n",
    "    all_y_data = np.cumsum(np.sum([np.pad(a, (0, max_len-len(a)), 'constant') for a in all_y_data], axis=0))\n",
    "    plt.plot(all_x_data[:7], all_y_data[:7], color=colors[i], label='All MIMIC')\n",
    "\n",
    "closed_markers = [None, 'o', '^', 's']\n",
    "for i,closed_dataset in enumerate(closed_datasets.items()):\n",
    "    if closed_dataset[0] == 'UK Biobank':\n",
    "        # UK Biobank for comparison\n",
    "        start_year = int(list(closed_dataset[1].keys())[0])\n",
    "        y_data = [v for y,v in closed_dataset[1].items() if ((int(y) >= start_year) and (int(y) <= max_year))]\n",
    "        y_data = np.cumsum(y_data)\n",
    "        x_data = range(len(y_data))\n",
    "        plt.plot(x_data[:7], y_data[:7], color='k', linestyle='--', marker=closed_markers[i], label=closed_dataset[0])\n",
    "\n",
    "plt.xlabel('Years Since Publication', fontsize=14)\n",
    "plt.ylabel('Total Number of Publications', fontsize=14)\n",
    "handles, labels = plt.gca().get_legend_handles_labels()\n",
    "order = np.arange(len(labels)-1, -1, -1)\n",
    "legend = plt.legend([handles[i] for i in order], [labels[i] for i in order], loc='upper right', fontsize=12)\n",
    "legend.get_frame().set_alpha(1)\n",
    "plt.grid(zorder=-1, axis='y')\n",
    "plt.xlim([0,8])\n",
    "plt.tight_layout()\n",
    "# plt.savefig(os.path.join(SEARCH_RESULT_FOLDER, 'google_scholar', 'cumulative_line-plot_baseline.png'))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plot the growth of each DB adjusted from the start time and normalized by total funding received"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "colors = [\n",
    "    'cornflowerblue',\n",
    "    'lightsteelblue',\n",
    "    'dimgray',\n",
    "    'lightcoral',\n",
    "    'firebrick'\n",
    "]\n",
    "max_year = 2022\n",
    "ALL_MIMIC = True\n",
    "\n",
    "years = [int(y) for y in google_scholar_mimic_pubs[list(google_scholar_mimic_pubs.keys())[0]].keys()]\n",
    "db_order = ['mimic-i','mimic-ii','mimic-iii','mimic-iv','mimic-cxr']\n",
    "\n",
    "plt.figure(figsize=(8,6))\n",
    "\n",
    "if ALL_MIMIC:\n",
    "    all_x_data = []\n",
    "    all_y_data = []\n",
    "for i,db in enumerate(db_order):\n",
    "    for y,v in google_scholar_mimic_pubs[db].items():\n",
    "        if v != 0:\n",
    "            start_year = int(y)\n",
    "            break\n",
    "    y_data = [v for y,v in google_scholar_mimic_pubs[db].items() if ((int(y) >= start_year) and (int(y) <= max_year))]\n",
    "    y_data = np.cumsum(y_data)\n",
    "    if ALL_MIMIC:\n",
    "        all_y_data.append(y_data)\n",
    "    else:\n",
    "        x_data = range(len(y_data))\n",
    "        plt.plot(x_data, y_data, color=colors[i], label=db.upper())\n",
    "if ALL_MIMIC:\n",
    "    max_len = max([len(a) for a in all_y_data])\n",
    "    all_x_data = range(max_len)\n",
    "    all_y_data = np.cumsum(np.sum([np.pad(a, (0, max_len-len(a)), 'constant') for a in all_y_data], axis=0))\n",
    "    all_y_data = all_y_data/total_funding['MIMIC']\n",
    "    total_funds = int(total_funding['MIMIC'])\n",
    "    plt.plot(all_x_data, all_y_data, color=colors[i], label=f'All MIMIC: ${total_funds:,.2f}')\n",
    "\n",
    "closed_markers = [None, 'o', '^', 's']\n",
    "for i,closed_dataset in enumerate(closed_datasets.items()):\n",
    "    # UK Biobank for comparison\n",
    "    start_year = int(list(closed_dataset[1].keys())[0])\n",
    "    y_data = [v for y,v in closed_dataset[1].items() if ((int(y) >= start_year) and (int(y) <= max_year))]\n",
    "    y_data = np.cumsum(y_data)\n",
    "    x_data = range(len(y_data))\n",
    "    try:\n",
    "        total_funds = int(total_funding[closed_dataset[0]])\n",
    "        plt.plot(x_data, y_data/total_funding[closed_dataset[0]], color='k', linestyle='--', marker=closed_markers[i], label=f'{closed_dataset[0]}: ${total_funds:,.2f}')\n",
    "    except KeyError:\n",
    "        continue\n",
    "\n",
    "plt.xlabel('Years Since Publication', fontsize=14)\n",
    "plt.ylabel('Total Number of Publications / Total Funding', fontsize=14)\n",
    "handles, labels = plt.gca().get_legend_handles_labels()\n",
    "order = np.arange(len(labels)-1, -1, -1)\n",
    "legend = plt.legend([handles[i] for i in order], [labels[i] for i in order], fontsize=12)\n",
    "legend.get_frame().set_alpha(1)\n",
    "plt.grid(zorder=-1, axis='y')\n",
    "plt.xlim([0,8])\n",
    "plt.yscale('log')\n",
    "plt.tight_layout()\n",
    "# plt.savefig(os.path.join(SEARCH_RESULT_FOLDER, 'google_scholar', 'cumulative_line-plot_baseline.png'))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Compile all citations of MIMIC from Pubmed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "colors = [\n",
    "    'cornflowerblue',\n",
    "    # 'lightsteelblue',\n",
    "    'dimgray',\n",
    "    'lightcoral',\n",
    "    'firebrick'\n",
    "]\n",
    "all_dbs = [f for f in os.listdir(MIMIC_PUBMED_CITATION_FOLDER) if f.endswith('.csv')]\n",
    "\n",
    "plt.figure(figsize=(6,6))\n",
    "MIMIC_citations = {}\n",
    "for i,db in enumerate(all_dbs):\n",
    "    db_name = db.split('.')[0]\n",
    "    temp_df = pd.read_csv(os.path.join(MIMIC_PUBMED_CITATION_FOLDER, db))\n",
    "    pub_dates = sorted([datetime.datetime.strptime(d,'%Y/%m/%d') for d in temp_df['Create Date'].tolist()])\n",
    "    # if db_name == 'MIMIC-II':\n",
    "    #     pub_dates = pub_dates[1:]\n",
    "    plot_pub_dates = [(d-pub_dates[0]).days/365 for d in pub_dates]\n",
    "    plt.plot(plot_pub_dates, range(1,len(plot_pub_dates)+1), color=colors[i], label=f'{db_name}')\n",
    "    MIMIC_citations[db_name] = pub_dates\n",
    "plt.xlabel('Years Since Publication', fontsize=14)\n",
    "plt.ylabel('Cummulative Citations', fontsize=14)\n",
    "plt.legend(fontsize=12)\n",
    "# plt.yscale('log')\n",
    "ax = plt.gca()\n",
    "ax.tick_params(which='major', labelsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Get the monthly rate of MIMIC citations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[2008    0]\n",
      " [2009    0]\n",
      " [2010    0]\n",
      " [2011    0]\n",
      " [2012    0]\n",
      " [2013    0]\n",
      " [2014    0]\n",
      " [2015    0]\n",
      " [2016    2]\n",
      " [2017    5]\n",
      " [2018    7]\n",
      " [2019   14]\n",
      " [2020   21]\n",
      " [2021   36]\n",
      " [2022   39]\n",
      " [2023   46]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "all_monthly_counts = {}\n",
    "for db in MIMIC_citations.keys():\n",
    "    all_monthly_counts[db] = dict(Counter([(d.year,d.month) for d in MIMIC_citations[db]]))\n",
    "    # all_monthly_counts = sorted(Counter([(d.year,d.month) for d in MIMIC_citations[db]]).items(), key=lambda dd:dd[0][0])\n",
    "    # print(db, all_monthly_counts)\n",
    "\n",
    "# Find the average number of papers cited per month\n",
    "all_days = list(range(1,31+1))\n",
    "all_months = list(range(1,12+1))\n",
    "all_years = range(2008,2023+1)\n",
    "# citation_times = []\n",
    "# for y in all_years:\n",
    "#     for m in all_months:\n",
    "#         for d in all_days:\n",
    "#             try:\n",
    "#                 dd = datetime.datetime(y,m,d)\n",
    "#             except ValueError:\n",
    "#                 continue\n",
    "#             citation_times.append((y,m,d))\n",
    "citation_times = [(y,m) for y in all_years for m in all_months]\n",
    "\n",
    "total_monthly_citations = []\n",
    "average_monthly_citations = []\n",
    "for y,m in citation_times:\n",
    "    temp_monthly_citations = 0\n",
    "    for db in MIMIC_citations.keys():\n",
    "        try:\n",
    "            temp_monthly_citations += all_monthly_counts[db][(y,m)]\n",
    "        except KeyError:\n",
    "            temp_monthly_citations += 0\n",
    "    average_monthly_citations.append((y,temp_monthly_citations))\n",
    "    total_monthly_citations.append(temp_monthly_citations)\n",
    "\n",
    "buffer_months = 4\n",
    "average_monthly_citations = average_monthly_citations[:-buffer_months]\n",
    "total_monthly_citations = total_monthly_citations[:-buffer_months]\n",
    "\n",
    "average_monthly_citations = [np.mean([c for y,c in average_monthly_citations if y==yy]) for yy in all_years]\n",
    "print(np.array(list(zip(all_years, average_monthly_citations))).astype(int))\n",
    "\n",
    "plt.figure(figsize=(6,6))\n",
    "x_dates = [datetime.datetime(y,m,1) for y,m in citation_times]\n",
    "plt.plot(x_dates[:-buffer_months], total_monthly_citations, color='k')\n",
    "plt.xlabel('Date', fontsize=14)\n",
    "plt.ylabel('Monthly Citations', fontsize=14)\n",
    "# plt.legend(fontsize=12)\n",
    "# plt.yscale('log')\n",
    "ax = plt.gca()\n",
    "ax.tick_params(which='major', labelsize=12)\n",
    "plt.show()\n",
    "\n",
    "plt.figure()\n",
    "plt.bar(all_years, average_monthly_citations, color='k')\n",
    "ax = plt.gca()\n",
    "for yy,y in enumerate(all_years):\n",
    "    ax.text(y, average_monthly_citations[yy]+0.5, f'{average_monthly_citations[yy]:.0f}', horizontalalignment='center', color='k', fontweight='bold')\n",
    "plt.xlabel('Date', fontsize=14)\n",
    "plt.ylabel('Average Monthly Citations', fontsize=14)\n",
    "# plt.legend(fontsize=12)\n",
    "# plt.yscale('log')\n",
    "ax = plt.gca()\n",
    "ax.tick_params(which='major', labelsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2036"
      ]
     },
     "execution_count": 173,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Total papers cited\n",
    "np.sum([len(MIMIC_citations[k]) for k in MIMIC_citations])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.7.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}