Smoking Status Variable - modifying existing rules

In this tutorial, we will be using the smoking status example data and existing rulesets that will allow us to classify charts according to the following labels: Current smoker, Former smoker, Never smoked, or Not dictated.

  1. Download the smoking status example data.
    • text_data.csv
    • labels_train.csv
    • labels_valid.csv
  2. Download the existing smoking status rules.
    • After downloading the rules, extract the zipped file and save the rules to a folder. Remember the path to this folder! You will need it later in step 5.
  3. Upload the text data file.
    • From the Settings view, press on the Project Settings tab.
    • Press on the Data File button to add the smoking status text data file (text_data.csv).
    • Set the Data ID column to be 0.
    • Set the Data First Row to be 1.
    • Set the Data Column to be 1.
  4. Upload the labels files.
    • Still in the Project Settings tab, set the Create Train and Validation Set flag to be False. We don’t need to create train and validation sets, since we will be uploading our own train and validation labels.
    • Set Prediction Mode to be False.
    • Press on the folder icon next to Train Label File to upload the smoking status train data labels (labels_train.csv).
    • Press on the folder icon next to Valid Label File to upload the smoking status valid data labels (labels_valid.csv).
    • Set the Label ID Column to be 0.
    • Set the Label First Row to be 1.
  5. Set Rules folder file.
    • Still in the Project Settings tab, press on the folder icon next to Rules Folder. Set the rules folder to be the folder from Step 2 (i.e., the folder where you saved the smoking status rules).
    • Press on the Save Project Settings button.
  6. Load the variable rules.
    • Go to the Variable Settings tab.
    • In the dropdown menu for Current variable, you should see the smoking_status variable. Select it.
    • Press on the Save Variable Settings button.
  7. Set the classifier settings.
    • Press on the Classifier Settings tab.
    • Set the Classifier Type to RegexClassifier.
    • Set the Negative Label to Not dictated.
  8. View the existing rules.
    • Go to the Rules view.
    • You should see the Current smoker, Former smoker and Never smoked labels.
  9. Run the tool.
    • Press on the Run button.
    • The top pane will display misclassified charts (i.e., the label predicted by CHARTextract is not the same as the ground truth label).
  10. Refine the rules.
    • Keep in mind that the rules we are releasing were developed on data that may be different from yours. Thus, we will want to refine the rules
    • Press on the misclassified chart with ID 1003.
    • CHARTextract classified this chart as Current smoker, but its ground truth label is Former smoker.
    • If you press on the yellow highlighted text, you will see that CHARTextract detected the words “former smoker of 1 pack”, and this gave a score of 4 to the Current smoker label and a score of 3 to the Former smoker label.
    • The rules in their current state are not able to correctly classify this chart. Let’s fix this.
    • Go back to the rules view. Press on the Current smoker label.
    • Add a secondary Ignore rule to the second Primary rule (Rule #2). In the text input field, add the following: former. Press on the dropdown menu next to appears, then score, and select Appears Before 2. This rule will be ignored if the word former appears before it.
    • Re-run the tool by pressing on the Run button.
    • You’ll notice that now chart with ID 1003 no longer shows up in the misclassified instances.

Further exercises: