A noval 4D graph temporal brain network model for EEG-based depression detection [0.03%]
一种基于EEG的抑郁症检测的新颖4D图形时间脑网络模型
Priyanka Gautam,Nisha Chaurasia
Priyanka Gautam
Major Depressive Disorder (MDD) represents a multifaceted and widespread mental health condition marked by substantial alterations in brain connectivity and neural dynamics, causing physiological stress. Accurate diagnosis via electroenceph...
PLETHSOMNet: automated identification of insomnia using deep neural network technique with photoplethysmography (PPG) signals [0.03%]
基于光电容积脉搏波描记信号的失眠自动识别深度神经网络模型(PLETHSOMNet)
Manisha Ingle,Labhesh Popatkar,Ankit Bhurane et al.
Manisha Ingle et al.
Purpose: Insomnia is a common sleep disorder, that causes difficulty in sleeping, staying asleep, or having non-restorative sleep. It often leads to daytime fatigue and impacts individuals' well-being and daily functionin...
Self-supervised fusion of clinical expertise and interpersonal skills for enhanced physician recommendation [0.03%]
基于自监督学习的临床技能和沟通能力融合的医生推荐模型
Wei Wang,Zhi-Chang Zhang,Yang Li et al.
Wei Wang et al.
For online medical consultation platforms, it is essential to recommend physicians with clinical expertise and interpersonal skills to improve patient satisfaction and clinical outcomes. Current physician recommendation is focused primarily...
Construction and application of a traditional Chinese medicine syndrome differentiation and treatment model grounded in knowledge distillation and reinforcement learning [0.03%]
基于知识蒸馏和强化学习的中医证候辨治模型构建及应用研究
Xinyu Wang,Xiaohe Sun,Jilong Shen et al.
Xinyu Wang et al.
Objective: This study endeavors to develop an intelligent diagnosis and treatment model for Traditional Chinese Medicine (TCM) syndrome differentiation and treatment, characterized by robust reasoning capabilities and exc...
An ECG early prediction algorithm integrating autonomic imbalance and repolarization energospectral shift [0.03%]
自主神经失衡与复极化能量光谱偏移融合的心电图早期预测算法
Jieshuo Zhang,Yilin Chang,Peng Xiong et al.
Jieshuo Zhang et al.
Purpose: Syncope is a transient loss of consciousness and increased fall risk due to cerebral hypoperfusion, often triggered by prolonged upright posture. Clinically, differential diagnosis largely relies on clinical mani...
Development and application of an intelligent management and home care system for geriatric diseases under the 'Internet Plus' model: big data-based risk prediction and personalized intervention [0.03%]
基于大数据的“互联网+”老年疾病智能管理和居家照护系统研发及应用：风险预测和个性化干预
Yan Zhu,Yuejia Ru,Juan Xie et al.
Yan Zhu et al.
Under the "Internet Plus" model, this study aims to develop a proof‑of‑concept intelligent decision‑support system for elderly disease risk assessment, with a specific focus on Alzheimer's Disease (AD). The primary objective is to evalua...
A unsupervised data-driven characterization of cardiovascular disease by self-organizing maps (SOM) approach [0.03%]
基于自组织映射(SOM)的无监督心血管疾病数据驱动表征研究
Omar Avalos,Milagros Contreras,Nayeli Areli Pérez-Padilla et al.
Omar Avalos et al.
Cardiovascular diseases (CVD) are among the leading causes of mortality worldwide due to genetic predisposition and lifestyle factors. Proper diagnosis of cardiovascular diseases is crucial to provide early-stage treatments. Conventional di...
From EHR chaos to clinical clarity: enhancing foundational encoders with task-specific attention for domain-oriented representation learning in downstream clinical applications [0.03%]
从EHR混乱到临床清晰：通过任务特定注意机制增强基础编码器以实现面向领域的表示学习在下游临床应用中的应用
Ibtihaj Ahmad,Jing Qu,Qi Zhang et al.
Ibtihaj Ahmad et al.
Electronic health records (EHRs) contain rich clinical information; however, they pose challenges for representation learning due to long free-text notes, domain shift, irregular structure, incomplete, and sparse fields. To address these ch...
Fine-grained evaluation of a domain-specific Q&A dataset to support trustworthy medical language models [0.03%]
细致评估领域特定的问答数据集以支持可信的医学语言模型
Rafael da C Fonseca,Ricardo A Rios,Rodrigo Castaldoni et al.
Rafael da C Fonseca et al.
The effective use of Large Language Models (LLMs) for generating coherent and informative content in specialized domains has largely been driven by the development of robust evaluation strategies. Based on this assumption, we introduce Hemo...
An explainable hybrid deep-learning and machine learning framework for automatic coeliac disease detection from duodenal endoscopy images [0.03%]
一种可解释的混合深度学习和机器学习框架自动检测十二指肠内镜图像中的乳糜泻
Souaad Hamza-Cherif,Adil Gaouar,Zineb Aziza El Aouaber et al.
Souaad Hamza-Cherif et al.
Purpose: Coeliac disease (CD) remains underdiagnosed because current diagnostic procedures rely on invasive biopsy, expert-dependent interpretation, and visually subtle endoscopic signs. This study aims to develop an expl...