Improving the performance of physiologic hot flash measures with support vector machines
نویسندگان
چکیده
منابع مشابه
Improving the performance of physiologic hot flash measures with support vector machines.
Hot flashes are experienced by over 70% of menopausal women. Criteria to classify hot flashes from physiologic signals show variable performance. The primary aim was to compare conventional criteria to Support Vector Machines (SVMs), an advanced machine learning method, to classify hot flashes from sternal skin conductance. Thirty women with > or =4 hot flashes/day underwent laboratory hot flas...
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Most midlife women have hot flashes. The conventional criterion (≥2 μmho rise/30 s) for classifying hot flashes physiologically has shown poor performance. We improved this performance in the laboratory with Support Vector Machines (SVMs), a pattern classification method. We aimed to compare conventional to SVM methods to classify hot flashes in the ambulatory setting. Thirty-one women with hot...
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ژورنال
عنوان ژورنال: Psychophysiology
سال: 2009
ISSN: 0048-5772,1469-8986
DOI: 10.1111/j.1469-8986.2008.00770.x