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Statistical Diagnosis of Multiple Sclerosis
Author(s) -
Ikeda Masato
Publication year - 1982
Publication title -
psychiatry and clinical neurosciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.609
H-Index - 74
eISSN - 1440-1819
pISSN - 1323-1316
DOI - 10.1111/j.1440-1819.1982.tb00269.x
Subject(s) - multiple sclerosis , discriminative model , medicine , disease , pathology , artificial intelligence , computer science , psychiatry
A statistical diagnostic method for multiple sclerosis (MS) was developed by using the history and clinical findings of 92 cases of MS and 168 cases of other diseases from which the disease has to be differentiated. The method developed consisted of two diagnostic procedures; the first based upon the discriminative function using 12 items of symptoms, signs or other features, while the second upon the maximum likelihood method utilizing the patterns of appearance of each of 38 items. When applied to the nationwide series of MS cases, the first diagnostic procedure diagnosed 96.6% of the probable cases, and 97.3% of Devic's disease cases, as MS. A successive application of the second procedure yielded the corresponding figures 80.4, 70.1%.