'update pages'

docs/Approach.html

@@ -13,7 +13,7 @@
 
 <title>Medical Imaging Extension Model</title>
 
-<script src="site_libs/header-attrs-2.25/header-attrs.js"></script>
+<script src="site_libs/header-attrs-2.24/header-attrs.js"></script>
 <script src="site_libs/jquery-3.6.0/jquery-3.6.0.min.js"></script>
 <meta name="viewport" content="width=device-width, initial-scale=1" />
 <link href="site_libs/bootstrap-3.3.5/css/cosmo.min.css" rel="stylesheet" />
@@ -372,16 +372,15 @@ <h1 class="title toc-ignore"><img src="images/ohdsi40x40.png"></img>Medical
 
 
 <p><br></p>
+<div id="representation" class="section level2">
+<h2><strong>Representation</strong></h2>
 <p>The medical imaging extension proposal represents imaging
 characteristics through two new tables—Image_occurrence and
 Image_features. <img
 src="https://github.com/jinwooyoon/edi_test/assets/84831718/8be9ce62-9f1b-408f-9af8-687237fd20d1" /></p>
-<p><br></p>
 <p><img
-src="https://github.com/jinwooyoon/edi_test/assets/84831718/e9df1b32-e57a-4bc0-ba6f-74afde55bdf9" /></p>
+src="https://github.com/jinwooyoon/ImageWG/assets/84831718/223c1512-2124-400d-84bb-c054ddbb8d29" /></p>
 <p><br></p>
-<div id="representation" class="section level2">
-<h2><strong>Representation</strong></h2>
 </div>
 <div id="schema" class="section level2">
 <h2><strong>Schema</strong></h2>

docs/background.html

@@ -13,7 +13,7 @@
 
 <title>Background</title>
 
-<script src="site_libs/header-attrs-2.25/header-attrs.js"></script>
+<script src="site_libs/header-attrs-2.24/header-attrs.js"></script>
 <script src="site_libs/jquery-3.6.0/jquery-3.6.0.min.js"></script>
 <meta name="viewport" content="width=device-width, initial-scale=1" />
 <link href="site_libs/bootstrap-3.3.5/css/cosmo.min.css" rel="stylesheet" />
@@ -288,6 +288,7 @@ <h1 class="title toc-ignore"><img src="images/ohdsi40x40.png"></img>Background</
 </div>
 
 
+<p><br></p>
 <p>The Medical Imaging Working Group (MI WG) for the OHDSI community was
 formed in 2021, comprised of imaging research scientists and
 observational health researchers familiar with OMOP CDM. The working
@@ -302,7 +303,6 @@ <h1 class="title toc-ignore"><img src="images/ohdsi40x40.png"></img>Background</
 other phenotypes. A prototype using CT lung nodules was developed and
 demonstrated at the 2023 Society of Imaging Informatics in Medicine
 (SIIM) conference Hackathon.</p>
-<p><br> <br></p>
 
 
 

docs/index.html

@@ -13,7 +13,7 @@
 
 <title> OHDSI Medical Image WG</title>
 
-<script src="site_libs/header-attrs-2.25/header-attrs.js"></script>
+<script src="site_libs/header-attrs-2.24/header-attrs.js"></script>
 <script src="site_libs/jquery-3.6.0/jquery-3.6.0.min.js"></script>
 <meta name="viewport" content="width=device-width, initial-scale=1" />
 <link href="site_libs/bootstrap-3.3.5/css/cosmo.min.css" rel="stylesheet" />
@@ -371,6 +371,7 @@ <h1 class="title toc-ignore"><img src="images/ohdsi40x40.png"></img>
 </div>
 
 
+<p><br></p>
 <div id="mission" class="section level2">
 <h2><strong>Mission</strong></h2>
 <p>The OHDSI Medical Imaging Working Group aims to represent medical

docs/site_libs/header-attrs-2.24/header-attrs.js

@@ -0,0 +1,12 @@
+// Pandoc 2.9 adds attributes on both header and div. We remove the former (to
+// be compatible with the behavior of Pandoc < 2.8).
+document.addEventListener('DOMContentLoaded', function(e) {
+  var hs = document.querySelectorAll("div.section[class*='level'] > :first-child");
+  var i, h, a;
+  for (i = 0; i < hs.length; i++) {
+    h = hs[i];
+    if (!/^h[1-6]$/i.test(h.tagName)) continue;  // it should be a header h1-h6
+    a = h.attributes;
+    while (a.length > 0) h.removeAttribute(a[0].name);
+  }
+});

rmd/Approach.Rmd

@@ -10,24 +10,18 @@ output:
 
 <br>
 
-The medical imaging extension proposal represents imaging characteristics through two new tables—Image_occurrence and Image_features. 
-![](https://github.com/jinwooyoon/edi_test/assets/84831718/8be9ce62-9f1b-408f-9af8-687237fd20d1)
-
-<br>
-
+## **Representation**
 
 
+The medical imaging extension proposal represents imaging characteristics through two new tables—Image_occurrence and Image_features. 
+![](https://github.com/jinwooyoon/edi_test/assets/84831718/8be9ce62-9f1b-408f-9af8-687237fd20d1)
 
 
-![](https://github.com/jinwooyoon/edi_test/assets/84831718/e9df1b32-e57a-4bc0-ba6f-74afde55bdf9)
+![](https://github.com/jinwooyoon/ImageWG/assets/84831718/223c1512-2124-400d-84bb-c054ddbb8d29)
 
 
 <br>
 
-## **Representation**
-
-
-
 
 ## **Schema**
 

rmd/background.Rmd

@@ -2,10 +2,9 @@
 title: '<div><img src="images/ohdsi40x40.png"></img>Background</div>'
 output: html_document
 ---
-The Medical Imaging Working Group (MI WG) for the OHDSI community was formed in 2021, comprised of imaging research scientists and observational health researchers familiar with OMOP CDM. The working group evaluated standard vocabularies, defined fields containing key imaging events, and identified limitations of the model. The working group started with the R-CDM in the development of the medical imaging extension. Imaging researchers across the field were consulted to gather requirements and gain insights into the structure and usability of the proposed model. The principal clinical use case focused on longitudinal tracking of multiple lung nodules. Important attributes included CT acquisition parameters, nodule diameter, location, density, shape, and other phenotypes. A prototype using CT lung nodules was developed and demonstrated at the 2023 Society of Imaging Informatics in Medicine (SIIM) conference Hackathon.
-
 
 <br>
-<br>
+
+The Medical Imaging Working Group (MI WG) for the OHDSI community was formed in 2021, comprised of imaging research scientists and observational health researchers familiar with OMOP CDM. The working group evaluated standard vocabularies, defined fields containing key imaging events, and identified limitations of the model. The working group started with the R-CDM in the development of the medical imaging extension. Imaging researchers across the field were consulted to gather requirements and gain insights into the structure and usability of the proposed model. The principal clinical use case focused on longitudinal tracking of multiple lung nodules. Important attributes included CT acquisition parameters, nodule diameter, location, density, shape, and other phenotypes. A prototype using CT lung nodules was developed and demonstrated at the 2023 Society of Imaging Informatics in Medicine (SIIM) conference Hackathon.
 
 

rmd/index.Rmd

@@ -8,7 +8,7 @@ output:
           collapsed: false
 ---
 
-
+<br>
 
 ## **Mission**