Development of reference systems for automatic identification of clinical isolates of bacteria

The reported work describes experiments on automatic identification based on a material of 636 clinical isolates of bacteria. It is shown that three different and mutually independent automatic identification principles produce almost identical identification conclusions. It is also shown that an automatic procedure which continuously corrects the basic classification gives results which are independent of the classification background. Automatic correction logics develop conventionally-based, as well as numerically-based initial reference systems toward almost similar solutions. This may indicate that automated identification methods based on numerical classifications possess general validity.