Bayesian Approaches To The Cold Start Problem

John Cook explains what you can do with data-driven applications when you don’t yet have the data:

How do you operate a data-driven application before you have any data? This is known as the cold start problem.

We faced this problem all the time when I designed clinical trials at MD Anderson Cancer Center. We used Bayesian methods to design adaptive clinical trial designs, such as clinical trials for determining chemotherapy dose levels. Each patient’s treatment assignment would be informed by data from all patients treated previously.

But what about the first patient in a trial? You’ve got to treat a first patient, and treat them as well as you know how. They’re struggling with cancer, so it matters a great deal what treatment they are assigned. So you treat them according to expert opinion. What else could you do?

Read on for John’s solution.

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