The invention relates to the technical field of acute and critical
disease auxiliary evaluation, particularly discloses an acute and critical
disease auxiliary evaluation method and
system based on clinical data, and aims to realize early warning of acute and critical diseases by monitoring and analyzing physiological parameters of a patient in real time. The method specifically comprises the steps that
heart rate and
blood pressure data of a patient are collected regularly and subjected to
standardization processing; calculating characteristic values such as
heart rate change rate,
blood pressure change rate and correlation coefficients thereof; calculating a comprehensive
score by using a weighted summation method, comparing the comprehensive
score with a preset threshold value, and judging whether the patient is in a high-risk state or not; a
logistic regression algorithm is adopted to construct a prediction model, and the accuracy is verified through a
training set and a
test set; the trained model is used for predicting new data, an alarm mechanism is triggered to inform
medical staff when a patient is judged to be at a high risk, evaluation results and
processing measures of each time are recorded, and
patient risk management archives are established, the accuracy and timeliness of acute and critical
disease diagnosis can be improved, and powerful support is provided for
clinical decision making.