This invention relates to the field of medical
artificial intelligence technology and discloses an intelligent assessment and
early warning system for extubation indications in tracheostomy patients. The
system includes a disturbance response acquisition module, a
state evolution trajectory construction module, a trajectory topology alignment module, an
implicit knowledge transfer module, a counterfactual deduction module, and an extubation decision output module. By applying multi-band micro-
airflow disturbances to detect
airway dynamic stability, it constructs a
patient state evolution trajectory, performs topological alignment with a historical case
database, transfers implicit experience from similar cases, and uses counterfactual deduction to determine the optimal intervention timing and measures, generating extubation decision suggestions and risk warning information. This invention achieves a leap from passive observation to
active detection, and from individual assessment to the transfer of collective wisdom, providing a precise and quantitative scientific basis for extubation decisions.