Chest X-Ray Medical Diagnosis with Deep Learning

In this notebook we will explore medical image diagnosis by building a state-of-the-art chest X-ray classifier using Keras.

The notebook will walk through some of the steps of building and evaluating this deep learning classifier model. In particular, we will:

• Pre-process and prepare a real-world X-ray dataset
• Use transfer learning to retrain a DenseNet model for X-ray image classification
• Learn a technique to handle class imbalance
• Measure diagnostic performance by computing the AUC (Area Under the Curve) for the ROC (Receiver Operating Characteristic) curve
• Visualize model activity using GradCAMs