The invention discloses a multilayer
cloud computing framework coordinated integrated reduction method for gestational-age newborn brain medical records. The multilayer
cloud computing framework coordinated integrated reduction method comprises the steps of firstly constructing a multilayer MapReduce coordinated neuro-subpopulational structure, extracting each neuro-subpopulational elite optimal weighted margin WCi, adaptively dividing a large-scale brain
medical record tissue attribute to n neuro-subpopulations which co-evolute through the MapReduce, and acquiring optimal dividing curved surfaces of different brain
medical record tissues; and designing a neural
network model with a five-layer structure, constructing an elite
energy matrix NSMP, performing integrated coordinated reduction of a brain
medical record curved surface Sub-curvei by each neuro-subpopulation optimal energy elite Elitist-leaderi, obtaining the optimal reduced set Redi<Ensemble> of a respective divided curved surface, and finally extracting a
global optimal attribute reduced set Red<Ensemble> of the brain medical
record tissue. According to the multilayer
cloud computing framework coordinated integrated reduction method, the reduction efficiency and the reduction efficiency for the gestational-age newborn brain medical records in a
big data environment are quickly improved through the multilayer MapReduce frame and coordinating with the neuro-subpopulational elite in a cloud computing environment. Furthermore the multilayer cloud computing framework coordinated integrated reduction method for the gestational-age newborn brain medical records has an important meaning for brain medical
record selection, role extraction,
clinical decision supporting service, etc.