Sex differences in brain MRI using deep learning toward fairer healthcare outcomes [0.03%]
基于深度学习的磁共振脑成像性别差异研究助力更公平的医疗健康结果预测
Mahsa Dibaji,Johanna Ospel,Roberto Souza et al.
Mahsa Dibaji et al.
This study leverages deep learning to analyze sex differences in brain MRI data, aiming to further advance fairness in medical imaging. We employed 3D T1-weighted Magnetic Resonance images from four diverse datasets: Calgary-Campinas-359, O...
Editorial: Computational modeling and machine learning methods in neurodevelopment and neurodegeneration: from basic research to clinical applications [0.03%]
主编评论：神经发育和神经退行性疾病的计算建模与机器学习方法：从基础研究到临床应用
Noemi Montobbio,Roberto Maffulli,Anees Abrol et al.
Noemi Montobbio et al.
Simulated synapse loss induces depression-like behaviors in deep reinforcement learning [0.03%]
模拟突触丢失在深度强化学习中诱发类似抑郁症的行为
Eric Chalmers,Santina Duarte,Xena Al-Hejji et al.
Eric Chalmers et al.
Deep Reinforcement Learning is a branch of artificial intelligence that uses artificial neural networks to model reward-based learning as it occurs in biological agents. Here we modify a Deep Reinforcement Learning approach by imposing a su...
Systematic review of cognitive impairment in drivers through mental workload using physiological measures of heart rate variability [0.03%]
基于心率变异性生理指标的工作记忆负荷下驾驶员认知缺损的系统性综述研究
Mansoor S Raza,Mohsin Murtaza,Chi-Tsun Cheng et al.
Mansoor S Raza et al.
The intricate interplay between driver cognitive dysfunction, mental workload (MWL), and heart rate variability (HRV) provides a captivating avenue for investigation within the domain of transportation safety studies. This article provides ...
Facial emotion recognition using deep quantum and advanced transfer learning mechanism [0.03%]
基于深度量子和先进迁移学习机制的面部情感识别
Shtwai Alsubai,Abdullah Alqahtani,Abed Alanazi et al.
Shtwai Alsubai et al.
Introduction: Facial expressions have become a common way for interaction among humans. People cannot comprehend and predict the emotions or expressions of individuals through simple vision. Thus, in psychology, detecting...
BrainNet: an automated approach for brain stress prediction utilizing electrodermal activity signal with XLNet model [0.03%]
脑网络：利用电导率活动信号和XLNet模型进行脑压力预测的自动方法
Liao Xuanzhi,Abeer Hakeem,Linda Mohaisen et al.
Liao Xuanzhi et al.
Brain stress monitoring has emerged as a critical research area for understanding and managing stress and neurological health issues. This burgeoning field aims to provide accurate information and prediction about individuals' stress levels...
Latent dynamics of primary sensory cortical population activity structured by fluctuations in the local field potential [0.03%]
初级感觉皮层群体活动的潜在动态变化由局部场电位波动决定
Audrey Sederberg,Aurélie Pala,Garrett B Stanley
Audrey Sederberg
Introduction: As emerging technologies enable measurement of precise details of the activity within microcircuits at ever-increasing scales, there is a growing need to identify the salient features and patterns within the...
Multi-stage semi-supervised learning enhances white matter hyperintensity segmentation [0.03%]
多阶段半监督学习增强白质高信号分割
Kauê T N Duarte,Abhijot S Sidhu,Murilo C Barros et al.
Kauê T N Duarte et al.
Introduction: White matter hyperintensities (WMHs) are frequently observed on magnetic resonance (MR) images in older adults, commonly appearing as areas of high signal intensity on fluid-attenuated inversion recovery (FL...
Data-centric automated approach to predict autism spectrum disorder based on selective features and explainable artificial intelligence [0.03%]
基于选择性特征和可解释人工智能的自闭症谱系障碍数据为中心的自动化预测方法
Asma Aldrees,Stephen Ojo,James Wanliss et al.
Asma Aldrees et al.
Autism spectrum disorder (ASD) is a neurodevelopmental condition marked by notable challenges in cognitive function, understanding language, recognizing objects, interacting with others, and communicating effectively. Its origins are mainly...
A combinatorial deep learning method for Alzheimer's disease classification-based merging pretrained networks [0.03%]
基于合并预训练网络的阿尔茨海默病分类组合深度学习方法
Houmem Slimi,Ala Balti,Sabeur Abid et al.
Houmem Slimi et al.
Introduction: Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline, memory loss, and impaired daily functioning. Despite significant research, AD remains incurable, highl...