Computational approaches for understanding the diagnosis and treatment of Parkinson's disease
作者： Stephen L. Smith , Michael A. Lones , Matthew Bedder , Jane E. Alty , Jeremy Cosgrove
DOI: 10.1049/IET-SYB.2015.0030
关键词:
摘要: This study describes how the application of evolutionary algorithms (EAs) can be used to motor function in humans with Parkinson's disease (PD) and animal models PD. Human data is obtained using commercially available sensors via a range non-invasive procedures that follow conventional clinical practice. EAs then classify human for uses, including diagnosis monitoring. New results are presented demonstrate also fruit flies without genetic mutations cause by measurements proboscis extension reflex. The case made computational approach applied across studies PD lays way evaluation existing new drug therapies truly objective way.
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