Fuzzy classification of patient state with application to electrodiagnosis of peripheral polyneuropathy.

A methodology which accounts for uncertainty or imprecision in experimental observations and both norm and pathology definitions is developed on the basis of a distance measure between fuzzy numbers. These fuzzy numbers may represent, respectively, the measurements, norm, and pathology. The distance measure, called normalized fuzzy pathology index (NFPI), evaluates the difference of distance between observed experimental values for a given patient and norm on the one hand, and pathology on the other hand.

Machine learning in quantitative histopathology.

The role of expert systems functioning as process controllers in learning image understanding systems is discussed. Numeric learning systems already have found a number of applications in cytologic and histopathologic diagnosis. Depending on the required capabilities, systems of increasing complexity are needed.