The invention relates to the technical field of
health risk assessment, in particular to a
postmenopausal osteoporosis risk prediction and traditional Chinese and
western medicine intervention
management system. The
system quantifies the trend risk of the
bone mineral density through the deviation change of the
bone mineral density risk value in
time sequence, and combines the initial
bone mineral density risk to divide the group and analyze and identify the risk degree of the group;
coupling the drop fluctuation characteristics of hormones with the change of bone
metabolism markers to obtain the comprehensive metabolic risk influence degree; determining the comprehensive influence degree of
osteoporosis by utilizing the group comprehensive bone
mineral density risk degree dynamic adjustment and combining the external risk influence degree and the comprehensive metabolic risk influence degree; and based on the
osteoporosis comprehensive influence degree of the sample data, training a neural
network model to carry out risk prediction. According to the method, the
risk model is constructed by considering the multi-dimensional influence of
hormone metabolism and behavioral habits of the postmenopausal patient and the multi-dimensional
coupling evaluation value, so that the risk prediction accuracy is improved, and more comprehensive and reliable data support is provided for
bone health management of
postmenopausal women.