Pre-Diagnosis of Osteoporosis Using Probabilistic Neural Networks

Osteoporosis is a skeletal disorder characterized by low bone density and micro-architectural deterioration of bony tissue. Dual-energy x-ray absorptiometry (DEXA) uses x-ray beams at two photon energies to estimate bone mineral density (BMD). This method has been applied extensively to detect osteoporosis. Due to the radiation disadvantage of the DEXA test, alternatively, an artificial intelligence-based decision support system was aimed. The system to be performed will be used as a preliminary diagnosis method for osteoporosis. For this, the probabilistic neural network (PNN) was used from 70 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.