The research on CPA diagnosis application basing on some Bayesian classifiers
Bei Hui, Lin Ji · 2013
Cerebellopontine angle(CPA) masses comprise about 8-10% of all intracranial neoplasm. Preoperative diagnosis of a CPA region mass is mainly based on imaging. MRI is the best method for diagnosing the CPAM. But MRI can't diagnose the different masses accurately. Many computer aided diagnose (CAD) technologies were developed to help radiologists to improve the diagnostic performance. The medical cases in the experiment were from West China Hospital. The experiment validates efficiency and effective of the some kinds Bayesian classifiers by 0-1 Error and RMSE. The result of experiment shows that Bayesian Classification model can classify CPAM effectively.