Classification of fine-motoric disturbances in Wilson's disease using artificial neural networks.
Patients suffering from Wilson's disease are divided into several types according clinical symptoms only at time of manifestation. Thereby two main subgroups exist: neurologic and non-neurologic types. After long-term therapy the neurological symptoms occurring in hepatolenticular degeneration may be improved but frequently with remaining fine-motoric disturbances which should be used for evaluation of the actual patient state. These disturbances are difficult to assess in an exact and objective manner by clinical examination. Therefore we measured fine-motoric passive and active abilities based on a standardized test set using the VSCOPE-system. The parallel evaluation of all fine-motoric data using an artificial neural network leads to a reclassification of these patients based on actual fine-motoric abilities but not reflecting the clinical classification at time of manifestation.
Hermann
W
W
Clinic of Neurology, University Leipzig, Leipzig, Germany.
Wagner
A
A
Kühn
H-J
HJ
Grahmann
F
F
Villmann
T
T
D000328:Adult; D000368:Aged; D001479:Basal Ganglia / Q000503:physiopathology; D002531:Cerebellum / Q000503:physiopathology; D016000:Cluster Analysis; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004185:Disability Evaluation; D005260:Female; D006527:Hepatolenticular Degeneration / Q000145:classification* / Q000175:diagnosis* / Q000503:physiopathology; D006801:Humans; D008297:Male; D008875:Middle Aged; D009048:Motor Skills / Q000502:physiology; D009068:Movement / Q000502:physiology; D016571:Neural Networks, Computer; D009460:Neurologic Examination; D014202:Tremor / Q000175:diagnosis / Q000209:etiology / Q000503:physiopathology