Osteoporosis classification using fuzzy rule based and neural networks

Most bone densitometry ultrasound devices measure only single predefined peripheral skeletal site. We propose a classification system to study the ability of combining speed of sound (SOS) measured at multiple bone sites to differentiate subjects with osteoporosis fractures from normal subjects based on fuzzy logic and neural networks systems. Classification rates were found to be 100% for training set and 97% for testing set for a dataset of 66 subjects