Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0030567 (Parkinson's disease)
 63,064 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Neuropathological studies show that about 20% of all patients suffering from an acinetic-rigid syndrome can not be given the diagnosis of idiopathic Parkinson's disease. Among these non-idiopathic Parkinson-syndromes the corticobasal degeneration (CBD) can be regarded as a separate disease entity. The pathological findings of moderate predominantly frontal and parietal cerebral atrophy, cortical Pick-cells and specific corticobasal inclusion bodies are considered valuable features which support the diagnosis. The clinical Characteristics of CBD are demonstrated in 3 patients including an acinetic-rigid syndrome, limb apraxia and "alien limb"-syndrome, as well as reflex myoclonus. Eye movement disorders, dementia and other rare symptoms may also be present. Electrophysiological reflex-testing helps to corroborate diagnosis. These findings and a summary which includes the previously published cases of CBD show that CBD in most cases can be diagnosed intra vitam.
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PMID:[Corticobasal degeneration. The significance of clinical criteria for establishing the diagnosis]. 780 63

The Phasic Electromyographic Metric (PEM) has been recently introduced as a sensitive indicator to differentiate Parkinson's Disease (PD) patients from controls, non-PD patients with a history of Rapid Eye Movement Disorder (RBD) from controls, and PD patients with early and late stage disease. However, PEM assessment through visual inspection is a cumbersome and time consuming process. Therefore, a reliable automated approach is required so as to increase the utilization of PEM as a reliable and efficient clinical tool to track PD progression. In this study an automated method for the detection of PEM is presented, based on the use of signal analysis and pattern recognition techniques. The results are promising indicating that an automatic PEM identification procedure is feasible.
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PMID:Phasic Electromyographic Metric detection based on wavelet analysis. 2438 39