The invention discloses a mild behavioral disorder
cognitive decline prediction method based on multi-
modal image fusion, and relates to the technical field of mild
cognitive impairment prediction. According to the method, feature vectors of different
modes are spliced to form a joint
feature matrix, redundant information is eliminated through
principal component analysis, and main variation components are reserved; inputting the
feature set after dimension reduction into a prediction model based on
machine learning, optimizing hyper-parameters through
cross validation, and training a classifier so as to identify a
cognitive decline risk mode of the patient with the mild behavioral disorder; multi-
modal image data are received in real time through a standardized API interface, a prediction
algorithm is automatically executed, and a report including individualized risk scores, confidence intervals,
risk level classification and
interpretability analysis is generated; the report is output in a structured format, so that a clinician can quickly refer to the report in the diagnosis process, meanwhile, the report is supported to be exported in a PDF or electronic health
record format, and seamless integration with an existing
medical information system is ensured.