Inkjet-Printed Graphene Electrodes on a Plastic Armband for Mobile Electrocardiography [0.03%]
用于移动心电图的塑料臂带上的喷墨打印石墨烯电极
Saygun Guler,Seyed Sajjad Mirbakht,Melih Can Tasdelen et al.
Saygun Guler et al.
Drop-on-demand inkjet printing has shown great potential for wearable health monitoring applications because of its ability to directly pattern on flexible substrates that can conform to curved surfaces such as the skin. Surface biopotentia...
Toward Effective Technology Support in DCTs: Insights from the Trials@Home Proof-of-Concept Trial RADIAL [0.03%]
远程居家临床试验技术支持的有效性探讨——来自居家试验试点项目RADIAL的启示
Theresa Weitlaner,Dimitrios Giannikopoulos,Bart Lagerwaard et al.
Theresa Weitlaner et al.
Decentralized clinical trials (DCTs) increasingly rely on digital tools such as wearable devices, mobile applications, and online platforms to enable remote data collection and participant engagement. While these technologies offer opportun...
Interpretable Feature Selection and Hybrid Deep Learning Models for Depressive Symptoms Prediction from Wearable Device Data [0.03%]
基于可解释特征选择和混合深度学习模型的情绪障碍预测方法研究
Jaehoon Ko,Somin Oh,Doljinsuren Enkhbayar et al.
Jaehoon Ko et al.
Early detection and prediction of Depressive Symptoms is essential for improving mental health outcomes. This study proposes a hybrid deep learning and machine learning framework that utilizes tabular data collected from wearable devices, i...
Operationalizing Large Language Models for Clinical Research Data Extraction: Methods, Quality Control, and Governance [0.03%]
临床研究数据提取的大规模语言模型操作化：方法、质量控制与治理
Lin Chen,Rui He,Puxuan Lu et al.
Lin Chen et al.
Methods This narrative review drew on targeted searches of PubMed/MEDLINE and arXiv (January 2020–October 2025), verification of peer-reviewed versions via ACL Anthology for selected preprints, and citation tracking of...
Bridging Neural Topology and Affective Computing: Graph Attention for EEG Emotion Recognition [0.03%]
基于脑电的情绪识别中的图注意力模型
Wenyang Yang,Jingrui Yuan,Bingnan Duan et al.
Wenyang Yang et al.
Electroencephalography (EEG) offers high temporal resolution and strong physiological validity for emotion recognition. However, complex spatial organization and inter-subject variability present major modeling challenges. Graph-based spati...
Comorbidity Classification from Clinical Free-Text using Large Language Models: Application to Sleep Disorder Patients [0.03%]
基于大型语言模型的临床自由文本共病分类及其在睡眠障碍患者中的应用研究
Yihan Deng,Fabio Dennstädt,Irina Filchenko et al.
Yihan Deng et al.
Patients presenting to neurology clinics commonly have a complex history of comorbidities and partially documented health trajectories, making it essential to reliably extract comorbidity information from historical records. However, existi...
Early Detection and Surveillance of Infectious Disease Outbreaks in Nigeria : Integrating Nigerian Pidgin English (NPE) into the EPIWATCH® Platform [0.03%]
尼日利亚传染病暴发的早期检测和监测：将尼日利亚皮金英语(NPE)整合到EPIWATCH®平台中
Omolara Kolawole,Ashley Quigley,Abrar A Chughtai et al.
Omolara Kolawole et al.
This study aimed to integrate Nigerian Pidgin English (NPE) into the Artificial Intelligence system EPIWATCH®, with the aim of providing early detection and enhanced surveillance of infectious disease outbreaks in Nigeria. The widespread u...
Advancing Medical Safety in AI Systems: Reflections on Reverse Prompting for Subtle Misinformation Detection [0.03%]
关于反向提示的反思：用于细微 misinformation 检测的AI系统中的医学安全性研究
Weihao Cheng,Zekai Yu,Feiwei Qin
Weihao Cheng
Optimizing Large Language Model Responses to Medical Queries: a Cross-sectional Study On the Effective Use of Chatgpt for Cancer-related Questions [0.03%]
大型语言模型在医学查询中的优化回应：关于有效使用ChatGPT解答癌症相关问题的横断面研究
Xinran Shao,Yihan Sun,Xingai Ju et al.
Xinran Shao et al.
Large language models (LLMs) are increasingly used for medical advice; despite this, their response readability and quality remain suboptimal. Current research focuses on evaluating LLM outputs, with little investigation into practical opti...