The invention provides an auxiliary detection
system for diagnosing Alzheimer's
disease, which relates to the technical field of classification diagnosis of Alzheimer's
disease, and comprises a
data acquisition module, a
data processing module, a
feature extraction module, a diagnosis model module and a
report generation module, according to the method, four types of core data including
clinical information, scale scores, MRI images and
blood biomarkers are integrated, the core dimension of Alzheimer's
disease diagnosis is covered, so that the
pathological evolution of AD from molecular
abnormality to structural damage can be more comprehensively captured by utilizing collaborative analysis of multi-
modal features, and the diagnosis accuracy of the Alzheimer's disease is improved. The problem of
missed diagnosis or misdiagnosis caused by single
modal data is avoided, and the diagnosis accuracy is improved. And secondly, aiming at the heterogeneity problem of image data and
blood marker data, a standardized
processing technology is adopted, so that the consistency of data of different sources and different batches is ensured, the influence of equipment difference and experimental error is eliminated, and a reliable guarantee is provided for model input.