The invention provides a cardiovascular and cerebrovascular
disease risk prediction method and
system, and relates to the technical field of
data processing.The method comprises the steps that real-time physiological parameters of a target user are obtained, and the real-time physiological parameters comprise the
ambulatory blood pressure fluctuation rate, the serum
lipoprotein level, the
heart rate variability
frequency domain index and the
sleep apnea hypopnea index; the method comprises the following steps: preprocessing real-time physiological parameters, extracting instantaneous waveform features of
blood pressure signals by adopting
wavelet transform, and extracting features related to health conditions, including
blood pressure level, blood fat level,
blood sugar level, electrocardiogram abnormal indexes and
cardiac ultrasound abnormal indexes, to form a
feature vector set; according to the method, the real-time physiological parameters are acquired, the
feature vector set is formed through preprocessing, the
krill swarm
algorithm is used for optimization, the three-
level fusion model is constructed, finally, the cardiovascular and cerebrovascular
disease risk degree of the target user is accurately evaluated, early warning information is output, and the accuracy and timeliness of cardiovascular and cerebrovascular
disease risk prediction are effectively improved.