Use of electronic patient data storage for evaluating and setting the risk category of late effects in childhood cancer survivors.

Automated algorithms can be used to categorize childhood cancer survivors efficiently and reliably into late effect risk groups. This further enables automatized compilation of appropriate individual late effect follow-up plan for all survivors.