Diagnosis of Parkinson's disease using evolutionary algorithms
Diagnosis of Parkinson's disease using evolutionary algorithms
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DOI：
10.1007/s10710-007-9043-9
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发表时间：
2007-12-01
影响因子：
2.6
通讯作者：
Playfer, Jeremy R.
中科院分区：
文献类型：
--
作者：
Smith, Stephen L.;Gaughan, Patrick;Playfer, Jeremy R.
本文描述了进化算法的新颖应用，以区分帕金森病患者和年龄匹配的对照者对简单图形复制任务的反应。众所周知，帕金森病的可靠诊断非常困难，据报道误诊率高达 25%。本文描述的方法旨在区分患者和对照的笔运动的速度曲线，以识别可能表明帕金森症状运动迟缓的区分伪影。研究结果针对 12 名帕金森病患者和 10 名年龄匹配的对照者。使用一半患者和年龄匹配的对照反应开发了一种算法，然后成功地使用该算法对剩余的反应进行正确分类。测试数据还采用了更严格的“留一”策略，取得了令人鼓舞的结果。
This paper describes the novel application of an evolutionary algorithm to discriminate Parkinson's patients from age-matched controls in their response to simple figure-copying tasks. The reliable diagnosis of Parkinson's disease is notoriously difficult to achieve with misdiagnosis reported to be as high as 25% of cases. The approach described in this paper aims to distinguish between the velocity profiles of pen movements of patients and controls to identify distinguishing artifacts that may be indicative of the Parkinson's symptom bradykinesia. Results are presented for 12 patients with Parkinson's disease and 10 age-match controls. An algorithm was evolved using half the patient and age-matched control responses, which was then successfully used to correctly classify the remaining responses. A more rigorous "leave one out" strategy was also applied to the test data with encouraging results.