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Titlebook: Digital Health and Wireless Solutions; First Nordic Confere Mariella S?rest?niemi,Pantea Keikhosrokiani,Jarmo Conference proceedings‘‘‘‘‘‘

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發(fā)表于 2025-3-21 18:14:50 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Digital Health and Wireless Solutions
副標(biāo)題First Nordic Confere
編輯Mariella S?rest?niemi,Pantea Keikhosrokiani,Jarmo
視頻videohttp://file.papertrans.cn/280/279370/279370.mp4
概述This book is open access, which means that you have free and unlimited access
叢書名稱Communications in Computer and Information Science
圖書封面Titlebook: Digital Health and Wireless Solutions; First Nordic Confere Mariella S?rest?niemi,Pantea Keikhosrokiani,Jarmo  Conference proceedings‘‘‘‘‘‘
描述.This two-volume set constitutes the refereed proceedings of the First Nordic Conference on , Digital Health and Wireless Solutions, NCDHWS 2024, held in Oulu, Finland, during May 7–8, 2024...The 51 full papers included in this book together with 7 short papers were carefully reviewed and selected from 100 submissions. They were organized in topical sections as follows:..Part I: Remote Care and Health Connectivity Architectures in 6G Era.- User Experience and Citizen Data.- Digitalization in Health Education.- Digital Health Innovations.- Digital Care Pathways...Part II: Clinical Decision Support and Medical AI.- Digital Care Pathways.- Novel Sensors and Bioinformatics.- Health Technology Assessment and Impact Evaluation.- Wireless Technologies and Medical Devices...This book is open access...?.
出版日期Conference proceedings‘‘‘‘‘‘‘‘ 2024
關(guān)鍵詞Open Access; digital health; eHealth; telemedicine; mobile applications; medical informatics; biosensors; m
版次1
doihttps://doi.org/10.1007/978-3-031-59091-7
isbn_softcover978-3-031-59090-0
isbn_ebook978-3-031-59091-7Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightThe Editor(s) (if applicable) and The Author(s) 2024
The information of publication is updating

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B. Lind,G. Blikra,H. Breivik,N. M. Ulvikand a change of?≥1?mmol/liter in lactate level. Na?ve Bayes, J48 Decision Tree, Logistic Regression, Random Forest, and Logistic Model Tree (LMT) classifiers were evaluated for lactate trend prediction. LMT algorithm outperformed other classifiers (AUC?=?0.803; AUPRC?=?0.921). J48 decision tree perf
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A. C. Yankaha,H. Menzel,V. Jagdschiancore. Sensitivity analysis was performed for two test set slice images in which different RA radiuses (4 pixels to 245) and movement artefacts, i.e., head tilt with rotation angles (0.2° to 3°), were generated. Artefact classification performance was excellent on the test set, as accuracy, average p
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Bedeutung neuer Vertriebskan?lech by using Design Science Research Methodology (DSRM). The design of the mobile application followed the principles of Persuasive Systems Design (PSD) model, which encompass a clear definition of the main task, user interaction through dialogue, system credibility, and social support, aiming to hel
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https://doi.org/10.1057/9781137392558ration of additional sensors and improves signal analysis efficiency. While the architecture is conceptual, its feasibility has been evaluated through simulations targeting specific challenges in networked remote photoplethysmography (rPPG) systems. Additionally, we implemented a prototype to demons
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Retail Banking im Informationszeitalterprovide several benefits in the analysis of rich sensor data, but the existing studies still have critical limitations in explaining the underlying cognitive functions and demonstrating the capacity for differential diagnostics is still underway. Clinical utility of sensor-based diagnostic methods c
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Tobias Sch?fers,Hans-Christian Riekhofm a specific setup parameter combination, and subsequently tested with data from varied setup parameters. We observed high correlation levels (r?=?0.93?±?0.09) paired with high error (RMSE?=?163?±?100?mHg), suggesting potential inaccuracies in pressure estimation. We present the recorded signals and
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