Results 51 to 60 of about 38,919 (183)
Clinical Pharmacology &Therapeutics, EarlyView.Traditional dosing strategies often rely on a “one‐size‐fits‐all” paradigm, assuming an “average” patient with typical demographic and pharmacological characteristics. In reality, this often overlooks existing between‐patient variability and can lead to suboptimal drug exposure or toxicity. This issue is especially pronounced in pediatric patients, who
Zachary L. Taylor +12 more
wiley +1 more source
Artificial intelligence in preclinical epilepsy research: Current state, potential, and challenges
Epilepsia Open, EarlyView.Abstract Preclinical translational epilepsy research uses animal models to better understand the mechanisms underlying epilepsy and its comorbidities, as well as to analyze and develop potential treatments that may mitigate this neurological disorder and its associated conditions. Artificial intelligence (AI) has emerged as a transformative tool across
Jesús Servando Medel‐Matus +7 more
wiley +1 more source
Bayesian Multivariate Two‐Stage Volatility‐Return Models (MTS‐VR)
Journal of Forecasting, EarlyView.ABSTRACT This paper develops a class of models to capture the joint dynamics of asset returns and multivariate volatility. Owing to its two‐stage construction, this class is referred to as the multivariate two‐stage volatility‐return (MTS‐VR) model.
Zhenglyu Huang +2 more
wiley +1 more source
Geological Journal, EarlyView.This work advances landslide susceptibility mapping by incorporating short‐term trigger data with landscape susceptibility mapping. We also examine the importance of downsampling, watershed delineation and geospatial correlations in evaluating outcomes.
Kanta Kotsugi +3 more
wiley +1 more source
Focusing on the relevant probabilities in population assignment to identify and correct bias
The Journal of Wildlife Management, EarlyView.Understanding and calculating conditional probabilities is essential to avoid misinterpretation of population assignment results. We demonstrate how to calculate conditional probabilities for assignments, identify the conditions under which the ability to assign individuals accurately is poor, and provide suggestions on how to mitigate these issues ...
Alyssa Green +3 more
wiley +1 more source
Calibration‐Free Single‐Frame Super‐Resolution Fluorescence Microscopy
Laser &Photonics Reviews, EarlyView.A deep learning framework reconstructs super‐resolved fluorescence images from a single dense camera frame, without any prior calibration or knowledge of the microscope. Trained solely on synthetic data, it generalizes across imaging setups and conditions.
Anežka Dostálová +3 more
wiley +1 more source
Peskine Sixfolds and Debarre–Voisin Fourfolds With Associated Cubic Fourfolds
Mathematische Nachrichten, EarlyView.ABSTRACT We develop the notion of Peskine sixfolds with associated K3 surfaces and cubic fourfolds and work out numerical conditions for when these associations occur. In discriminant 24, the first family for which there is an associated cubic fourfold, we identify the cubic explicitly.
Corey Brooke +3 more
wiley +1 more source
Mathematical Methods in the Applied Sciences, EarlyView.We develop a full randomization of the classical hyper‐logistic growth model by obtaining closed‐form expressions for relevant quantities of interest, such as the first probability density function of its solution, the time until a given fixed population is reached, and the population at the inflection point.
Juan Carlos Cortés +2 more
wiley +1 more source
Otolaryngology–Head and Neck Surgery, EarlyView.Abstract Objective To evaluate the real‐world diagnostic performance of a multimodal large language model (LLM) for image‐based assessment of oral mucosal lesions compared with clinicians of varying expertise. Study Design Prospective international multicenter diagnostic accuracy study.
Luigi A. Vaira +32 more
wiley +1 more source
Supervised Protein Structure Classification Using Topological Persistence With DeltaFold
Proteins: Structure, Function, and Bioinformatics, EarlyView.ABSTRACT Recent advances in protein structure prediction have considerably increased the number of available structures, underscoring the need for scalable and accurate methods to compare and classify this huge amount of data. Current approaches based on sequence alignment or structural superposition often lack sensitivity and/or are computationally ...
Joseph Nardin‐Gennequin +3 more
wiley +1 more source