William L. Maner

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OBJECTIVE To use artificial neural networks (ANNs) on uterine electromyography (EMG) data to classify term/preterm labor/non-labor pregnant patients. MATERIALS AND METHODS A total of 134 term and 51 preterm women (all ultimately delivered spontaneously) were included. Uterine EMG was measured trans-abdominally using surface electrodes. "Bursts" of(More)
Diabetic gastroparesis is a disorder that predominantly affects women. However, the biological basis of this sex bias remains completely unknown. In this study we tested the hypothesis that a component of this effect may be mediated by the nitrergic inhibitory system of the enteric nervous system. Age-matched male and female Sprague-Dawley rats were studied(More)
OBJECTIVE The purpose of this study was to compare uterine electromyography of patients delivering>24 hours from measurement with laboring patients<or=24 hours from measurement. STUDY DESIGN Fifty patients (group 1: labor, n=24; group 2: antepartum, n=26) were monitored using transabdominal electrodes. Group 2 was recorded at several gestations. Uterine(More)
The present work seeks to determine if a particular non-linear analytic method is effective at quantifying uterine electromyography (EMG) data for estimating the onset of labor. Twenty-seven patients were included, and their uterine EMG was recorded non-invasively for 30 min. The patients were grouped into two sets: G1: labor, N = 14; G2: antepartum, N =(More)
AIMS Bilateral pelvic neurectomy (BPN) interferes with delivery in rats. This work measures the effect of BPN on uterine and abdominal electromyography (EMG) and pressure during gestation and delivery. METHODS Uterine EMG and intra-uterine pressure (IUP), as well as abdominal muscle EMG and intra-abdominal pressure (IAP), were recorded on days 19-24 in(More)
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