Diagnosis Classification Research for Disease of Osteoporosis Based on BP Neural Network

Objective To reduce the misdiagnosis rate of osteoporosis. A diagnostic classification facilitates rapid and accurate diagnosis. Methods We utilized the theory of BP neural network model to construct osteoporosis diagnosis classification model for analyzing osteoporosis assessment indicator system. BP neural network system is designed according to the indicator system. The artificial neural network was used to compute actual data of a large number of cases in Orthopaedics Department of General Hospital of Lanzhou Military Area Command. Results The error of the model was controlled within predetermined error range. It is demonstrated to be feasibile and accurate. Conclusion The diagnosis of osteoporosis by using BP neural network is feasible and effective.