Results 111 to 120 of about 20,375,797 (310)
Elevated Connectivity During Language Processing Is Associated With Cognitive Performance in SeLECTS
ABSTRACT Objective Self‐Limited Epilepsy with Centrotemporal Spikes (SeLECTS) is associated with language impairments despite seizures originating in the motor cortex, suggesting aberrant cross‐network interactions. Here we tested whether functional connectivity in SeLECTS during language tasks predicts language performance.
Wendy Qi +8 more
wiley +1 more source
Estimating controlled direct treatment effects on pain intensity using structural mean models
. Introduction:. Without valid inclusion of concurrent analgesic use, the primary analyses of pain intensity in pain randomized controlled trials (RCTs) may produce diminished estimated treatment effects. Methods:.
Rui Wang +3 more
doaj +1 more source
Machine Learning Models for Heart Attack Prediction
Abstract—This article presents a comprehensive analysis of machine learning models for heart attack prediction by employing various analytical techniques to gain insights into the structure and characteristics of the dataset. The exploration begins with an Exploratory Data Analysis (EDA) and delving into the distribution of individual features and the ...
Ibrahimli, Javad +3 more
openaire +1 more source
RNA Sequencing Resolves Cryptic Pathogenic Variants in Mitochondrial Disease
ABSTRACT Objective Mitochondrial diseases are the most common inherited metabolic disorders, characterized by pronounced clinical and genetic heterogeneity that complicates molecular diagnosis. Although DNA‐based sequencing approaches have become standard in genetic testing, up to half of patients remain without a definitive diagnosis.
Zhimei Liu +21 more
wiley +1 more source
ABSTRACT Background Cognitive impairment is a common non‐motor symptom in Multiple Sclerosis (MS), negatively affecting autonomy and Quality of Life (QoL). Innovative rehabilitation strategies, such as semi‐immersive virtual reality (VR) and computerized cognitive training (CCT), may offer advantages over traditional cognitive rehabilitation (TCR ...
Maria Grazia Maggio +8 more
wiley +1 more source
MolAnchor method for explaining compound predictions based on substructures
In medicinal chemistry, the impact of machine learning remains limited if predictions are not understood, which often precludes experimental follow-up. Therefore, chemically intuitive approaches that aid in model understanding and interpretation at the ...
Alec Lamens, Jürgen Bajorath
doaj +1 more source
Memory and Resting‐State Connectivity in Acute Transient Global Amnesia: A Case–Control fMRI Study
ABSTRACT Background and Objectives Transient global amnesia (TGA) is a striking model of isolated amnesia. While hippocampal lesions are well described, the network‐level mechanisms and the precise neuropsychological profile remain debated. Our objective was thus to characterize functional and neuropsychological correlates of acute TGA and their ...
Elias El Otmani +10 more
wiley +1 more source
Early Clinical, Imaging, and Pathological Characteristics of SRPK3/TTN‐Digenic Myopathy
ABSTRACT Objective SRPK3/TTN‐digenic myopathy was recently established as a skeletal muscle myopathy caused by digenic inheritance. This study characterizes the early clinical presentation of SRPK3/TTN‐digenic myopathy in one previously reported and seven newly identified pediatric patients.
Rotem Orbach +23 more
wiley +1 more source
ABSTRACT Objective We aim to comprehensively analyze how regional tumor and edema characteristics are associated with clinical presentations and survival outcomes in a large cohort of glioblastoma patients. Methods Patients with IDH‐wildtype glioblastoma who received brain MRI from 2010 to 2023 were included.
Daniel J. Zhou +16 more
wiley +1 more source
Screening Routine Clinical Notes for Epilepsy Surgery Candidates Using Large Language Models
ABSTRACT Objective Epilepsy surgery is severely underutilized despite proven efficacy, with substantial under‐referral of eligible patients in routine clinical practice. This study evaluated the potential role of large language models (LLMs) as decision‐support tools for screening unstructured clinical notes to identify epilepsy surgery candidates and ...
Uriel Fennig +9 more
wiley +1 more source

