The invention relates to the technical field of medical
data analysis, in particular to a
kidney injury
prediction system based on
big data, which comprises a physiological
data processing module, a fluctuation analysis construction module, a dynamic weight evaluation module, a cross-domain
data scheduling module and a risk
trend prediction module. According to the method, through
timestamp standardization and continuous recombination of the
acute kidney injury physiological data, the consistency of multi-source
monitoring data in the time dimension is ensured, drifting and
dislocation are eliminated, the
time sequence integrity is improved, fluctuation points of serum
creatinine and
urine volume are extracted, sensitive time slices are recognized, and high-risk time point early warning is achieved; a
rate change comparison mechanism is introduced, a physiological factor weight sequence is generated, factor influence evaluation is enhanced, uploading frequency and a time
delay state are combined, high-reliability nodes are screened,
data continuity and real-time performance are improved, index trend deviation is tracked, a mode
label is generated, and timeliness and accuracy of
renal function change prediction are improved.