Publications by authors named "M A Louter"
Article Synopsis
- The study explored the potential of supervised machine learning applied to ECG data for real-time sleep monitoring in pediatric intensive care, which is currently not available.
- Researchers analyzed polysomnography recordings from 90 non-critically ill children, developing various machine learning models to classify sleep states based on derived features from the ECG data.
- Results showed that the models achieved moderate to good accuracy, especially in classifying two and three sleep states, with the XGBoost model performing best overall, highlighting the method's promise for bedside use.
Study Objectives: We examined the association between pulse transit time (PTT) and obstructive sleep apnea (OSA) in children with syndromic craniosynostosis (SCS), where OSA is a common problem and may cause cardiorespiratory disturbance.
Methods: A retrospective study of children (age < 18 years) with SCS and moderate-to-severe OSA (ie, obstructive apnea-hypopnea index ≥ 5) or no OSA (obstructive apnea-hypopnea index < 1) who underwent overnight polysomnography. Children without SCS and normal polysomnography were included as controls.
AbstractVocal production learning (the capacity to learn to produce vocalizations) is a multidimensional trait that involves different learning mechanisms during different temporal and socioecological contexts. Key outstanding questions are whether vocal production learning begins during the embryonic stage and whether mothers play an active role in this through pupil-directed vocalization behaviors. We examined variation in vocal copy similarity (an indicator of learning) in eight species from the songbird family Maluridae, using comparative and experimental approaches.
View Article and Find Full Text PDFAcute withdrawal of headache medication in chronic migraine patients with medication overuse may lead to a dramatic reduction in headache frequency and severity. However, the brain networks underlying chronic migraine and a favorable response to acute withdrawal are still poorly understood. The goal of the present study was to characterize the pattern of intrinsic magnetic resonance imaging (MRI) functional connectivity (FC) specific to chronic migraine and to identify changes in FC that characterize subjects with CM reverting to less frequent headaches.
View Article and Find Full Text PDFArticle Synopsis
- The study aims to create a straightforward index for sleep classification using electroencephalography data to address sleep disruption in pediatric intensive care units where real-time monitoring is unavailable.! -
- A retrospective analysis was performed at Erasmus MC Sophia Children's Hospital on polysomnography recordings from non-critically ill children between 2017 and 2021, evaluating sleep patterns across various age groups and frequency bands.! -
- The results indicated a strong performance of the developed sleep index, particularly with a gamma to delta power ratio, achieving balanced accuracy rates of up to 0.92 for two-state classifications in different age categories, suggesting it could facilitate automated sleep monitoring for children aged 6 months to 18 years.!