Writing

Notes on medical AI

For clinicians and students: the data, labels and evaluation that decide whether a model can be trusted.

The model is not the hard part

A melanoma AI that learned surgical ink, a cost label that missed need, an alert that is right 16% of the time and a sepsis model that drifted. Four questions anyone can ask about a medical AI tool, and why they are clinical questions.