  The present work develops ANAKIN: an Artificial iNtelligence bAsed model for
(radiation induced) cell KIlliNg prediction. ANAKIN is trained and tested over
513 cell survival experiments with different types of radiation contained in
the publicly available PIDE database. We show how ANAKIN accurately predicts
several relevant biological endpoints over a wide broad range on ions beams and
for a high number of cell--lines. We compare the prediction of ANAKIN to the
only two radiobiological model for RBE prediction used in clinics, that is the
Microdosimetric Kinetic Model (MKM) and the Local Effect Model (LEM version
III), showing how ANAKIN has higher accuracy over the all considered biological
endpoints. At last, via modern techniques of Explainable Artificial
Intelligence (XAI), we show how ANAKIN predictions can be understood and
explained, highlighting how ANAKIN is in fact able to reproduce relevant
well-known biological patterns, such as the overkilling effect.
