Heart disease risk diagnosis method based on deep convolutional neural network model
A neural network model and deep convolution technology, applied in the medical field, can solve problems such as failure to provide patients, satisfaction, and failure to realize active early warning of acute cardiac diseases, so as to reduce the risk of sudden cardiac acute diseases and improve expression ability Effect
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[0030]The following description serves to disclose the present invention to enable those skilled in the art to carry out the present invention. The embodiments in the following description are only examples, and those skilled in the art can think of other obvious modifications. The basic principles of the present invention defined in the following description can be applied to other embodiments, variations, improvements, equivalents and other technical solutions without departing from the spirit and scope of the present invention.
[0031] figure 1 A schematic flow chart showing the method for diagnosing acute cardiac diseases based on the deep convolutional neural network model of the present invention, according to the appended figure 1 A heart attack risk diagnosis method based on a deep convolutional neural network model provided by the present invention is characterized in that it comprises the following steps:
[0032] Step 1: Establish a heart attack risk prediction m...
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