Japanese Alzheimer’s Disease and Other Complex Disorders Diagnosis Based on Mitochondrial SNP Haplogroups
Figure 1
RBF network representation of the relations between individual mtSNPs and the AD patients. The input layer is the set of mtSNP sequences represented numerically (A, G, C, and T are converted to 1, 2, 3, and 4). The hidden layer classifies the input vectors into several clusters according to the similarities of individual input vectors. The determination of the output layer depends on which analysis is carried out. In the case of AD patients, 1 corresponds to AD patients and 0 corresponds to seven other classes of people. The other classes of people (PD patients, T2D patients, T2D patients with angiopathy, centenarians, semi-supercentenarians, non-obese young males, and obese young males) are carried out in a similar way. is the th input vector, TN is the maximum number of vectors (in this example, (), is the maximum number of mtSNPs (in this example, ), is the location vector, m is the number of basis functions, is the basis function, is the standard deviation, is the th weighting variable, and is the weighted sum function.
