  Anemia, for which erythropoiesis-stimulating agents (ESAs) and iron
supplements (ISs) are used as preventive measures, presents important
difficulties for hemodialysis patients. Nevertheless, the number of physicians
able to manage such medications appropriately is not keeping pace with the
rapid increase of hemodialysis patients. Moreover, the high cost of ESAs
imposes heavy burdens on medical insurance systems. An
artificial-intelligence-supported anemia control system (AISACS) trained using
administration direction data from experienced physicians has been developed by
the authors. For the system, appropriate data selection and rectification
techniques play important roles. Decision making related to ESAs poses a
multi-class classification problem for which a two-step classification
technique is introduced. Several validations have demonstrated that AISACS
exhibits high performance with correct classification rates of 72-87% and
clinically appropriate classification rates of 92-98%.
