This invention relates to the field of intelligent medical
data analysis technology, specifically to a method and
system for the intelligent prevention and control of venous thromboembolism in
hospitalized patients. The method involves acquiring static
medical record features and determining target test indicators; determining the target time window through a closed-loop adaptive mechanism driven by the fitting uncertainty of a
Gaussian process regression model; constructing a weighted
bipartite graph and removing
confounding factors based on the topological overlap of
pathological pathways to extract pure
thrombosis baseline scores and pure bleeding baseline scores; extracting the first and second derivatives of time-
series data and concatenating them with the pure baseline scores to construct a
dynamic feature vector; generating a baseline-driven adaptive boundary in a two-dimensional
phase plane; constructing a short-range predicted trajectory based on Taylor expansion and solving for the collision time; performing multi-objective game arbitration based on the time priority principle to generate prevention and control strategies; and achieving forward-looking joint decision-making in a dynamic conflicting
scenario of
thrombosis and bleeding risks.