  The idea of using computers to read medical scans was introduced as early as
1966. However, limits to machine learning technology meant progress was slow
initially. The Alexnet breakthrough in 2012 sparked new interest in the topic,
which resulted in the release of 100s of medical AI solutions on the market. In
spite of success for some diseases and modalities, many challenges remain.
Research typically focuses on the development of specific applications or
techniques, clinical evaluation, or meta analysis of clinical studies or
techniques through surveys or challenges. However, limited attention has been
given to the development process of improving real world performance. In this
tutorial, we address the latter and discuss some techniques to conduct the
development process in order to make this as efficient as possible.
