Label Generation Process

Once you've uploaded data and defined variables for your project, it's time to generate labels.

Each generation takes time and resources. To make the best use of them, we recommend an iterative process:

1. Generate Labels for one patient to check data and variable setup.
   1. Review labels for that patient.
   2. Add or remove variables if you'd like.
   3. Change variable definitions and instructions, optimizing the variable if you haven't yet.
   4. Repeat single patient generation as necessary until you’re satisfied.
2. Generate Labels for a Batch of patients.
   1. Review that batch in Label Review, making data edits as necessary. These edits will automatically be included when optimizing variables.
   2. Optimize the variables to get better results on future batches.
3. Continue generating and reviewing patients in Batches until all of your data is abstracted and reviewed.
   1. You can optimize variables at any point to apply the learnings from your reviewed data points to future generations.

Once you’ve reviewed a data point, Brim will not overwrite that data point when you do a new generation unless you explicitly instruct it to overwrite human-reviewed labels.

Best Practice: There is a tradeoff between time spent refining variables and time spent reviewing abstracted labels. We recommend shifting your focus to reviewing when the labels pass 90% accuracy.