title: [Research on the application of neural network to diagnosis of cardiopathy].
abstract: Neural networks can fit any nonlinear function. After drawing out several characteristic parameters from the three-dimension spectrum for high frequency QRS waves, we input them into the network and trained the network. In this way, we can get a m-dimension curved surface in the m-dimension space which is constructed by those parameters, and this curved surface divides the space into two parts: the unhealthiness and the health. Now, the network can automatically distinguish between the healthiness and the unhealthiness according to their three-dimension spectrum for high frequency QRS waves.
authors.affiliation: State Key Laboratory of Modern Acoustics, Institute of Biomedical Electronical Engineering, Electronic Science and Engineering Department, Nanjing University, Nanjing 210093, China. xbning@nju.edu.cn
authors.forename: Xinbao
authors.initials: X
authors.lastname: Ning
authors.forename: Xiaolin
authors.initials: X
authors.lastname: Huang
authors.forename: Yinlin
authors.initials: Y
authors.lastname: Xu
authors.forename: Guiming
authors.initials: G
authors.lastname: Han
mesh_terms: D000465:Algorithms; D003327:Coronary Disease / Q000175:diagnosis*; D004562:Electrocardiography; D006801:Humans; D007091:Image Processing, Computer-Assisted; D016571:Neural Networks, Computer