Results 161 to 170 of about 663,162 (276)

Research progress on the depth of anesthesia monitoring based on the electroencephalogram

open access: yesIbrain, Volume 11, Issue 1, Page 32-43, Spring 2025.
Electroencephalogram (EEG) can noninvasive, continuous, and real‐time monitor the state of brain electrical activity, and the monitoring of EEG can reflect changes in the depth of anesthesia (DOA). The development of artificial intelligence can enable anesthesiologists to extract, analyze, and quantify DOA from complex EEG data.
Xiaolan He, Tingting Li, Xiao Wang
wiley   +1 more source

Household Consumption Intentions by Income Group During Monetary Policy Easing and Tightening

open access: yesInternational Journal of Finance &Economics, EarlyView.
ABSTRACT We investigate how the monetary policy interest rate affects Brazilian households' consumption intentions under two distinct regimes: monetary easing and tightening cycles. Using data from low‐ and high‐income households, we assess both the magnitude and the dynamics of this relationship.
Helder Ferreira de Mendonça   +1 more
wiley   +1 more source

Preterm assisted vaginal births and associated maternal and neonatal outcomes: A retrospective study in a tertiary hospital

open access: yesInternational Journal of Gynecology &Obstetrics, EarlyView.
Abstract Objectives This study compares maternal and neonatal outcomes between preterm vacuum and forceps‐assisted vaginal births and evaluates preterm outcomes between those <34 + 0 weeks gestation to those ≥34 + 0. Methods This study is a single‐center retrospective cohort study of all singleton assisted vaginal births during 2014–2021. Delivery data
Caroline Leps   +7 more
wiley   +1 more source

From Reactive to Proactive Volatility Modeling With Hemisphere Neural Networks

open access: yesJournal of Applied Econometrics, EarlyView.
ABSTRACT We revisit maximum likelihood estimation (MLE) for macroeconomic density forecasting through a novel neural network architecture with dedicated mean and variance hemispheres. Our architecture features several key ingredients making MLE work in this context.
Philippe Goulet Coulombe   +2 more
wiley   +1 more source

Forecasting Related Time Series

open access: yesJournal of Applied Econometrics, EarlyView.
ABSTRACT A collection of time series are “related” if they follow similar stochastic processes and/or they are statistically dependent. This paper proposes a related time series (RTS) forecasting model that exploits these relationships. The model's foundation is a set of univariate Gaussian autoregressions, one for each series, which are then augmented
Ulrich K. Müller, Mark W. Watson
wiley   +1 more source

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