Explainable AI in oncology: why black boxes have no place in your care
A look at how OncoXAI's models surface reasoning alongside predictions — and why we would rather be slower than opaque.

A model that says "high risk" without telling you why is a model that cannot be challenged — and in medicine, every claim must be challengeable.
How we show our work
Every prediction OncoXAI surfaces is paired with the specific features that drove it: imaging regions, lab values, genomic markers. Your oncologist can agree, disagree, or ask for more data.
Written by
Sana Okafor
Part of the OncoXAI medical team. All content is peer-reviewed by a board-certified oncologist.



