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 ...