AIMC Topic: Male

Clear Filters Showing 7291 to 7300 of 27433 articles

Metrics for evaluation of automatic epileptogenic zone localization in intracranial electrophysiology.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
INTRODUCTION: Precise localization of the epileptogenic zone is critical for successful epilepsy surgery. However, imbalanced datasets in terms of epileptic vs. normal electrode contacts and a lack of standardized evaluation guidelines hinder the con...

Explainable Deep Learning Approaches for Risk Screening of Periodontitis.

Journal of dental research
Several pieces of evidence have been reported regarding the association between periodontitis and systemic diseases. Despite the emphasized significance of prevention and early diagnosis of periodontitis, there is still a lack of a clinical tool for ...

Machine learning outperforms the Canadian Triage and Acuity Scale (CTAS) in predicting need for early critical care.

CJEM
STUDY OBJECTIVE: This study investigates the potential to improve emergency department (ED) triage using machine learning models by comparing their predictive performance with the Canadian Triage Acuity Scale (CTAS) in identifying the need for critic...

Enhancing Motor Imagery Classification with Residual Graph Convolutional Networks and Multi-Feature Fusion.

International journal of neural systems
Stroke, an abrupt cerebrovascular ailment resulting in brain tissue damage, has prompted the adoption of motor imagery (MI)-based brain-computer interface (BCI) systems in stroke rehabilitation. However, analyzing electroencephalogram (EEG) signals f...

Deep Learning Recognition of Paroxysmal Kinesigenic Dyskinesia Based on EEG Functional Connectivity.

International journal of neural systems
Paroxysmal kinesigenic dyskinesia (PKD) is a rare neurological disorder marked by transient involuntary movements triggered by sudden actions. Current diagnostic approaches, including genetic screening, face challenges in identifying secondary cases ...

Multiclass classification of Alzheimer's disease prodromal stages using sequential feature embeddings and regularized multikernel support vector machine.

NeuroImage
The detection of patients in the cognitive normal (CN), mild cognitive impairment (MCI), and Alzheimer's disease (AD) stages of neurodegeneration is crucial for early treatment interventions. However, the heterogeneity of MCI data samples poses a cha...

Application of Machine Learning and Deep Neural Visual Features for Predicting Adult Obesity Prevalence in Missouri.

International journal of environmental research and public health
This research study investigates and predicts the obesity prevalence in Missouri, utilizing deep neural visual features extracted from medium-resolution satellite imagery (Sentinel-2). By applying a deep convolutional neural network (DCNN), the study...

A Transcriptomics-Based Machine Learning Model Discriminating Mild Cognitive Impairment and the Prediction of Conversion to Alzheimer's Disease.

Cells
The clinical spectrum of Alzheimer's disease (AD) ranges dynamically from asymptomatic and mild cognitive impairment (MCI) to mild, moderate, or severe AD. Although a few disease-modifying treatments, such as lecanemab and donanemab, have been develo...

Enhancing puncture skills training with generative AI and digital technologies: a parallel cohort study.

BMC medical education
BACKGROUND: Traditional puncture skills training for refresher doctors faces limitations in effectiveness and efficiency. This study explored the application of generative AI (ChatGPT), templates, and digital imaging to enhance puncture skills traini...