11 Training a classification model to detect suspected tumors

This chapter covers

  • Using PyTorch DataLoaders to load data
  • Implementing a model that performs classification on our CT data
  • Setting up the basic skeleton for our application
  • Logging and displaying metrics

In the previous chapters, we set the stage for our cancer-detection project. We covered medical details of lung cancer, took a look at the main data sources we will use for our project, and transformed our raw CT scans into a PyTorch Dataset instance. Now that we have a dataset, we can easily consume our training data. So let’s do that!

11.1 A foundational model and training loop

We’re going to do two main things in this chapter. We’ll start by building the nodule classification ...

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