Pre-diagnosis of osteoporosis using the properties of biomedical signals

Osteoporosis is a skeletal disorder characterized by low bone intensity and micro-architectural corruption of osseous texture. Dual-Energy X-ray Absorptiometry (DEXA) uses x-ray beams at two photon energies to predict bone mineral intensity (BMD). This method has been applied extensively to determine osteoporosis. Due to the radiation disadvantage of the DEXA test, alternatively, an artificial intelligence-based decision support system is aimed. The system to be performed will be used as a preliminary diagnosis method for osteoporosis. For this reason, PNN, LVQ, MLNN-1, MLNN-2 are used from 150 patient's specific parameters. It has been observed that artificial neural networks can be used as a decision support system in the diagnosis of osteoporosis. Thanks to this study, the probability of the application of the DEXA test will be reduced to a minimum for all the patients who are suspected of having this disease.