The research then concentrated on the use of type 2 sets, initially in two application areas - community transport and medical imaging. However, what has been of particular interest is in the use of type 2 sets as pre-processors for neural network analysis of shin images. Stress fractures are usually partial fractures or cracks which result from the application of habitual, non-violent, repetitive stress which exceeds the existing functional capacity of the bones.
Diagnosis is based on imprecise data.
The approach taken was to describe the images using a questionnaire developed in conjunction with the expert and then present this data in a form suitable for analysis using Fuzzy ART and Fuzzy Min-Max. Of particular interest is whether type 2 sets offer any advantage over type 1 sets for preprocessing of the expert's interpretation of the images. No firm conclusions can be drawn from this single piece of work since there are many factors that can influence the outcome. Firstly, the neural network paradigms adopted are for unsupervised clustering, and depending on the order of presentation of data and the control parameters used, different clusters are selected. Also, whether adopting a type 1 or type 2 approach the knowledge engineer has to make decisions about membership functions.