The invention discloses a clinical tag labeling method,
system and equipment based on a standardized
time sequence and a medium, and relates to the technical field of clinical event fusion and dynamic tag generation, and the specific steps are as follows: obtaining clinical
event data of a patient from different clinical business systems in real time, dividing cycle attribution for the clinical
event data, and determining the clinical
event data; and establishing a dynamic weight calculation model to allocate dynamic weight values, establishing a periodic
clinical state inference model by adopting a
convolutional neural network and training the periodic
clinical state inference model, inputting weighted summary clinical feature vectors in a current patient period according to the trained periodic
clinical state inference model, and outputting clinical tags corresponding to patients. According to the invention, clinical
label labeling based on a standardized
time sequence is realized, multi-source clinical event data from different clinical business systems can be collected in real time, event weights are reasonably distributed through a dynamic weight calculation model, a periodic clinical state is deduced by using a
convolutional neural network, and clinical labels of patients are automatically generated.