Introduction: Logic Stages

Add a Logic Stage to your workflow to create dynamic paths for your data based on the annotations that your files contain. Logic stages let you create custom if/else statements or Rules to automatically manage the flow of your data.

For example, you can route content based on different factors: If your use case requires many stages, switch from a series of stages based on their content, or trigger webhooks based automation when specific classes are added to a file. Check out the guide below for inspiration on how you can inject Logic into your datasets.

How to set up

Setting up Logic Stages in your workflow is straightforward and intuitive:

1. How to set up

Setting up Logic Stages in your workflow is straightforward and intuitive:

2. How to set up

Setting up Logic Stages in your workflow is straightforward and intuitive:

1. Drag and drop the Logic stage into your workflow template.
2. Plug the stage into the previous workflow stage (where the files will be flowing from).
3. Place your Logic on to trigger the next specified workflow Stage. Any files that do not meet the criteria for a rule, they will be sent to the next specified workflow Stage. If they meet this criteria, they will be sent to the stage connected to it.

You can add multiple conditions to create more complex routing logic. The Logic stage evaluates conditions in order, so make sure to arrange them according to your workflow requirements.

Setting up custom rules

Custom rules give you powerful control over how your data flows through the system. You can define rules based on file attributes, annotations, confidence scores, or any other metadata available in your workflow.

Each rule consists of a condition and an action. When files match the condition, they are automatically routed to the specified destination. This automation eliminates manual sorting and ensures consistent processing.

Rules can be as simple or complex as needed. Start with basic conditions and gradually build more sophisticated logic as you become familiar with the system’s capabilities.

Automated routing of data

Once your rules are set, the system automatically routes data to the correct processing stage. This ensures that only high-quality, validated data moves forward in your clinical pipeline, reducing manual review time.

Comparing model performance with conditional logic

Logic Stages excel at managing model outputs with varying confidence levels. You can route predictions to different review queues based on confidence thresholds, ensuring quality control.

This conditional routing based on model performance creates an efficient human-in-the-loop system that balances automation with oversight, maximizing both accuracy and throughput.

Key takeaways

• Efficiency: Logic stages automate decision-making in your data pipeline.
• Control: Custom rules allow for granular control based on metadata and annotations.
• Accuracy: Automated routing improves efficiency and reduces manual errors.