title: Support Vector Machines to improve physiologic hot flash measures: application to the ambulatory setting.
abstract: 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 flashes underwent 24 h of ambulatory sternal skin conductance monitoring. Hot flashes were quantified with conventional (≥2 μmho/30 s) and SVM methods. Conventional methods had low sensitivity (sensitivity=.57, specificity=.98, positive predictive value (PPV)=.91, negative predictive value (NPV)=.90, F1=.60), with performance lower with higher body mass index (BMI). SVMs improved this performance (sensitivity=.87, specificity=.97, PPV=.90, NPV=.96, F1=.88) and reduced BMI variation. SVMs can improve ambulatory physiologic hot flash measures.
authors.affiliation: Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15213, USA. thurstonrc@upmc.edu
authors.forename: Rebecca C
authors.initials: RC
authors.lastname: Thurston
authors.forename: Javier
authors.initials: J
authors.lastname: Hernandez
authors.forename: Jose M
authors.initials: JM
authors.lastname: Del Rio
authors.forename: Fernando
authors.initials: F
authors.lastname: De La Torre
mesh_terms: D000328:Adult; D001185:Artificial Intelligence; D005260:Female; D005712:Galvanic Skin Response / Q000502:physiology*; D019584:Hot Flashes / Q000503:physiopathology*; D006801:Humans; D008875:Middle Aged; D018670:Monitoring, Ambulatory / Q000379:methods*; D047648:Perimenopause / Q000502:physiology*; D012680:Sensitivity and Specificity; D011795:Surveys and Questionnaires