wfwiggins · wfwiggins · Nov 15, 2018 · Nov 15, 2018
diff --git a/.gitignore b/.gitignore
@@ -0,0 +1 @@
+.ipynb_checkpoints/
diff --git a/HelloWorldDeepLearning.ipynb b/HelloWorldDeepLearning.ipynb
@@ -3,9 +3,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -304,7 +302,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.1"
+   "version": "3.6.6"
   }
  },
  "nbformat": 4,

diff --git a/README.md b/README.md
@@ -2,7 +2,7 @@
 
 Author: Paras Lakhani, paras.lakhani@jefferson.edu
 
-More details and a step-by-step guide for the tutorial can be found in the Journal of Digital Imaging Publication (ref:   ), which is the official journal of the Society of Imaging Informatics in Medicine (SIIM).
+More details and a step-by-step guide for the tutorial can be found in the Journal of Digital Imaging Publication [link to article](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5959832/), which is the official journal of the Society of Imaging Informatics in Medicine (SIIM).
 
 This is a high-level introduction into practical machine learning for purposes of medical image classification. 
 
@@ -23,7 +23,9 @@ You'll need a computer with the following installed:
 3) Jupyter (http://jupyter.org)
 4) Download the x-rays provided in .zip file 
 
-To make things easier, there is a convenient SIIM docker that has Tensorflow / Keras / Jupyterlab already installed, located here: https://github.com/ImagingInformatics/machine-learning/tree/master/docker-keras-tensorflow-python3-jupyter
+To make things easier...
+
+There is also a SIIM docker that has Tensorflow / Keras / Jupyterlab already installed, located here: https://github.com/ImagingInformatics/machine-learning/tree/master/docker-keras-tensorflow-python3-jupyter
 
 After your environment is set up, open the ipython notebook, and run the code!
 

diff --git a/data.zip b/data.zip
diff --git a/data/test.sh b/data/test.sh
@@ -0,0 +1,11 @@
+subdirs=$(ls -D ../Results/AllResults/*/)
+while read line; do
+    for subdir in $subdirs; do
+	filepath="../Results/AllResults/${subdir}${line}.png" 
+	if [ -e "$filepath" ]; then
+	        cp $filepath ./NonsinglezeroQA
+            else
+                echo "file not found in ${subdir}"
+        fi
+    done
+done < Nonsinglezero2012processed.txt
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