One of the most intriguing connections between biology and machine learning is in the learning ability of the adaptive immune system. If you abstract away the biology, it appears to be a very complex problem of classification: is something an invader or not? False positives cause autoimmune diseases. False negatives cause dangerous infections.

Just as in machine learning, we can use the concepts of sensitivity and specificity, positive and negative predictive values, classification, clustering, and feature extraction.

And we can also use the techniques to guide treatments.

How about using AdaBoost to train the immune system? Expose it only to the examples it initially misclassifies? There are so many places where these two fields can intersect…