We have, so far, used deep networks for image, text, and time series processing. While most of our examples were interesting and relevant, they weren't enterprise-grade. Now, we'll tackle an enterprise-grade problem—medical diagnosis. We make the enterprise-grade designation because medical data has attributes one does not typically deal with outside large enterprises, namely proprietary data formats, large native sizes, inconvenient class data, and atypical features.
In this chapter, we will cover the following topics:
- Medical imaging files and their peculiarities
- Dealing with large image files
- Extracting class data from typical medical files
- Applying networks "pre-trained" with non-medical data
- Scaling training to accommodate the scale typically with medical data
Obtaining medical data is a challenge on its own, so we...
