bluuebunny/crossref_metadata_2025_split huggingface dataset:
Discovering the Order‐Disorder Transition in Quinoline Intercalated Vanadium Oxide with Superior Calcium Storage via Polyhedral Distortion
Authors: Zhao Xu , Li Linyuan , Zhang Guobin , Yi Yong , Yang Tao , Han Cuiping , Li Baohua 
Published: May 2024

AbstractCalcium‐ion batteries (CIBs) are considered as potential next‐generation energy storage systems due to their abundant reserves and relatively low cost. However, irreversible structural changes and weak conductivity still hinder in current CIBs cathode materials. Herein, an organic molecular intercalation strategy is proposed, in which V2O5 regulated with quinoline, pyridine, and water molecules are studied as cathode material to provide fast ion diffusion channels, large storage host, and high conductivity for Ca ions. Among them, V2O5‐quinoline (QVO) owns the largest interplanar spacing of 1.25 nm and the V‐O chains are connected with organic molecular by hydrogen bond, which stabilizes the crystal structure. As a result, QVO exhibits a specific capacity of 168 mAh g−1 at 1 A g−1 and capacity retention of 80% after 500 cycles at 5 A g−1 than the other materials. Furthermore, X‐Ray diffraction and X‐ray absorption spectroscopy results reveal a reversible order‐disorder transformation mechanism of Ca2+ for QVO, which can make full use of the abundant active sites for high capacity and simultaneously achieve fast reaction kinetics for excellent rate performance. These results demonstrate that QVO is a promising cathode material for CIBs, providing more choices for the development of high‐performance CIBs.
Engineered shapes using electrohydrodynamic atomization for an improved drug delivery
Authors: Yu Deng‐Guang , Gong Wenjian , Zhou Jianfeng , Liu Yanan , Zhu Yunajie , Lu Xuhua 
Published: May 2024

AbstractThe shapes of micro‐ and nano‐products have profound influences on their functional performances, which has not received sufficient attention during the past several decades. Electrohydrodynamic atomization (EHDA) techniques, mainly include electrospinning and electrospraying, are facile in manipulate their products' shapes. In this review, the shapes generated using EHDA for modifying drug release profiles are reviewed. These shapes include linear nanofibers, round micro‐/nano‐particles, and beads‐on‐a‐string hybrids. They can be further divided into different kinds of sub‐shapes, and can be explored for providing the desired pulsatile release, sustained release, biphasic release, delayed release, and pH‐sensitive release. Additionally, the shapes resulted from the organizations of electrospun nanofibers are discussed for drug delivery, and the shapes and inner structures can be considered together for developing novel drug delivery systems. In future, the shapes and the related shape–performance relationships at nanoscale, besides the size, inner structure and the related structure–performance relationships, would further play their important roles in promoting the further developments of drug delivery field.This article is categorized under:
Therapeutic Approaches and Drug Discovery > Emerging Technologies
Expert Perspectives on Future 6G-Enabled Hospital Metaverse
Authors: Wang Fan , Jurva Risto , Ahokangas Petri , Yrjölä Seppo , Matinmikko-Blue Marja 
Published: May 2024

AbstractThis paper aims to understand the value-added services that the future 6G-enabled metaverse can and will bring to hospitals. This is important since most studies on 6G and the metaverse are heavily driven by technological solutions. Adopting a qualitative research approach, this paper collects experts’ opinions on the usage scenarios of the 6G-enabled metaverse in hospitals. Six use cases within hospital contexts have been identified from open-ended interviews. The analysis of each case reveals that 6G, as a general-purpose technology, offers the necessary capabilities to support the development of the metaverse in hospitals. The metaverse-enabled services are expected to design future smart hospitals and improve work processes and resource allocation in hospitals, while also promoting preventive healthcare and training and enhancing the quality of care in emergency, treatment, and rehabilitation. Consequently, the development of both metaverse and 6G will progress in tandem, hand in hand, offering local services in hospitals. From a value perspective, this paper contributes to the development of the 6G and metaverse in the hospital vertical by understanding the needs, capabilities, and key values of the future 6G-enabled hospital metaverse.
The Adoption of MyData-Based Health Applications Among Elderly Citizens in Nordic Countries and the UK
Authors: Jayathilake Chathurangani , Keikhosrokiani Pantea , Isomursu Minna 
Published: May 2024

AbstractThis study addresses a crucial gap in current literature by examining the use of MyData-based health apps among individuals aged 50 and above in the UK and Nordic nations. With the advancement of personalized health technologies, understanding the factors influencing adoption among the elderly is essential. The research provides insights tailored to this demographic within the broader framework of digital health adoption. The primary scientific objective was to identify technological and health-related factors influencing the willingness of senior adults (50 and above) to use MyData-based preventive healthcare applications. The conditions for adoption, technological considerations, health-related variables, willingness to share MyData, and demographic variations were explored. Grounded in the Universal Theory of Acceptance and Use of Technology (UTAUT2) and Health Protection Motivation components, the research employed a quantitative approach, integrating a new concept called sharing personal data into the framework. Data collection occurred through an online survey in the UK and the Nordic region, yielding 374 responses from the Nordic sample and 1165 from the UK sample, resulting in a cleaned dataset of 1016. Findings revealed the significance of willingness to share MyData for both the UK and Nordic regions, with performance expectancy emerging as an outstanding technological factor for the Nordic population, but not for the UK. Across nations and genders, self-efficacy is portrayed as a strong driver in health-related aspects. These contribute to academic knowledge and have societal value by guiding the development of digital health solutions for the elderly, ultimately improving their quality of life and health outcomes.
Digital Twins for Development of Microwave-Based Brain Tumor Detection
Authors: Särestöniemi Mariella , Singh Daljeet , Heredia Charline , Nikkinen Juha , von und zu Fraunberg Mikael , Myllylä Teemu 
Published: May 2024

AbstractDigital twins for different healthcare applications are currently being studied actively since they could revolutionize research on customized and personalized healthcare and enable realistic evaluations of new medical devices and applications in early phase. This paper presents a study on the development of digital twins aiming to be utilized for the development of microwave technique-based brain tumor detection. Realistic anatomical models of the digital twins were designed based on magnetic resonance images (MRI) scanned from the brain with brain tumor. These twins aim to correspond to the human brain and brain tumor in terms of size, shape, and tissue dielectric properties. Furthermore, developed digital twins include both phantom models for measurement emulation as well as corresponding simulation models designed using electromagnetic simulation software. By using the developed digital twins, our aim is to evaluate microwave-based sensing technique for brain tumor detection. Evaluations were carried out using flexible ultrawideband (UWB) antennas which would be beneficial for practical solutions. Our simulation and emulation results show that microwave technique with flexible antennas has high potential for brain tumor detection.
Enhancing Independent Auditory and Speechreading Training – Two Finnish Free Mobile Applications Constructed for Deaf and Hard of Hearing Children and Adults
Authors: Huttunen Kerttu , Kauramäki Jaakko , Pajo Kati , Saalasti Satu 
Published: May 2024

AbstractThe users of hearing technology often need auditory training for getting used to their hearing devices and maximally benefiting from them. Because auditory training given by professionals is only sparsely available, there is a great need for materials and applications with which self-training is possible. Moreover, deaf and hard-of-hearing persons need to improve their speechreading skills to help in speech reception and children to strengthen their reading skills. We describe the background, contents, construction and features of two Finnish free applications: Auditory Track for auditory training and Optic Track for speechreading (lip reading) training. Both can be used by children and adults, even though the Auditory Track is mainly aimed at adults and the Optic Track at primary school age children. The features of both applications include exercises carefully selected based on extensive knowledge of the acoustic and visual characteristics of speech. In addition, during the implementation of both applications, careful attention has been paid to the usability, accessibility, gamification and construction of feedback systems. The applications developed can be used in independent training, clinical use and research.
Social and Health Care Teachers’ Experiences of Implementing Multidisciplinary Specialisation Studies in a Digital Learning Environment
Authors: Naakka Hanna , Heinonen Jarmo , Männistö Merja , Perälä Sami , Rauha Anna , Paldanius Mika , Ahonen Outi , Sanerma Päivi 
Published: May 2024

AbstractThe aim of the study was to find out how teachers and project actors experienced the implementation of the specialisation education in a digital learning environment. The methods were triangulation with paired t-test, ANOVA and content analysis of qualitative data. The results showed a statistical difference between the responses after the first and second implementation of specialisation education. The overall results show that teachers and project actors demonstrate a strong commitment to producing and developing student-centred and work-life-centred online specialisation education.
Supporting Sense of Meaningful Life and Human Dignity in Digitally Assisted Physiotherapy Environment – Qualitative Secondary Research with Thematic Analyses and Inductive Synthesis
Authors: Sjögren Tuulikki , Korpi Hilkka 
Published: May 2024

AbstractThe goal of this secondary research was to create a model that aims at increasing the sense of meaningful life and human dignity in physiotherapy by utilizing remote and digital rehabilitation technologies, focusing on people with cerebrovascular accident (CVA) and multiple sclerosis (MS). The results of this qualitative research effort have been obtained using thematic analyses and inductive synthesis. Our primary research, which provides materials for the secondary analysis, is based on qualitative systematic literature reviews and a meta-synthesis of the perceived meaningfulness of physiotherapy. The outcome of the secondary analysis is a research-based model, which combines rehabilitees´ experiences and expectations towards physiotherapy, professionals’ competence needs, and the technological prerequisites for using digital rehabilitation technologies with CVA and MS rehabilitees. Maintenance of human dignity and promotion of the sense of meaningful life, and various issues related to them, were most meaningful for the rehabilitees. The essential prerequisites of meaningful use of re- mote and digital rehabilitation technologies in physiotherapy were enabling identification of the rehabilitees’ own current functioning, needs and goals, supporting their motivation and commitment, choosing relevant and meaningful activities, creating safe and variable environments, and enabling social interaction and relationships. As far as we know, this is the first model which combines neuro- logical rehabilitees’ experiences of physiotherapy with remote and digital technology’s potential. In the future, the usefulness of our novel research-based holistic and biopsychosocial physiotherapy model should be tested in real life situations.
Preliminary Study on Wellbeing and Healthcare Services Needs in Japan and Finland for Telehealth Solutions Based on Dwelling
Authors: Hyry Jaakko , Karppinen Pasi , Kobayashi Takumi , Anzai Daisuke 
Published: May 2024

AbstractThe Japanese and Finnish healthcare systems have several longstanding challenges from the scattered data in storing databases due to location sensitivity and sometimes unequal services for their users. In addition to the data itself, location plays another role for the citizens living in urban or rural areas. They suffer from different well-being outcomes as stress and sedentary lifestyles have presented negative impacts on the urban dwellers. As remote work and technological solutions have become more common, in this conceptual research, we explore the general healthcare and living area challenges and how to make services more equal to everyone. We also discuss the possible telehealth solutions and how, for example, wearable body sensors’ use could offer improvements to the availability and accessibility of healthcare services.
Closing the Loop for Controlled Substances Surveillance: A Field Study of the Usability and User Experience of an Integrated Electronic Narcotic Consumption
Authors: Häkkinen Annika , Viitanen Johanna , Savolainen Kaisa , Mäkinen Ville-Matti , Siven Mia , Lääveri Tinja , Tolonen Hanna M. 
Published: May 2024

AbstractThe distribution and handling of controlled substances (CSs), i.e., narcotics, is strictly regulated to decrease the risk of abuse and drug diversion. In Finland, hospital pharmacies are mandated to keep records of CS distribution and consumption in healthcare through a labor-intensive paper-based process. After implementing a new electronic health record (EHR) system, a large university hospital started to streamline the process by transferring the CS documentation process from paper to digital format. Although the benefits of digital archiving, surveillance, and consumption monitoring are self-evident from the hospital pharmacy’s perspective the advantages at wards remain less explored. Therefore, our goal was to explore the usability and user experience (UX) of the recently implemented electronic narcotic consumption card (eNCC) solution built into the EHR system, and the related workflows of nurses, pharmacists, and physicians. The field study consisted of two parts and was conducted using observation, interviews, and survey methods in two wards. Our findings suggest that the digitalized process enables reliable real-time documentation of CSs and improves process efficiency, particularly for oral tablets and capsules. Considering diverse end-users’ perspectives is crucial when assessing the practical benefits of newly implemented digital solutions targeted at several healthcare professional groups. This approach enables a broader understanding of UX; supports development efforts, including usability improvements; and facilitates broader implementation. More research is needed to analyze the long-term impacts of the digital CSs’ consumption documentation workflow and surveillance at different healthcare units.
A User-Centric Exploration of a Digital Health Experience
Authors: Haanpää Milka , Saraniemi Saila 
Published: May 2024

AbstractThis paper explores digital health experience through focus on the experiences of diabetics who utilize digital health technology in their daily diabetes management. Theoretically, the paper draws from research on digital experience and from theoretical discussions concerned with digital health. Empirically, it analyzes three multimodal datasets using reflective thematic analysis. Three interlinked themes – always on, co-creation through interaction, and it makes things so much easier – are revealed. These themes reveal the key characteristics of users’ digital health experiences and highlight how users shape their experiences in their daily lives. The study contributes theoretically to digital experience literature within which user-centric, longitudinal studies are scarce. Practically, it demonstrates to health professionals and developers how digital health technology becomes integrated into their users’ lives.
Using Machine Learning Methods to Predict the Lactate Trend of Sepsis Patients in the ICU
Authors: Arslantas Mustafa Kemal , Asuroglu Tunc , Arslantas Reyhan , Pashazade Emin , Dincer Pelin Corman , Altun Gulbin Tore , Kararmaz Alper 
Published: May 2024

AbstractSerum lactate levels are considered a biomarker of tissue hypoxia. In sepsis or septic shock patients, as suggested by The Surviving Sepsis Campaign, early lactate clearance-directed therapy is associated with decreased mortality; thus, serum lactate levels should be assessed. Monitoring a patient’s vital parameters and repetitive blood analysis may have deleterious effects on the patient and also bring an economic burden. Machine learning and trend analysis are gaining importance to overcome these issues. In this context, we aimed to investigate if a machine learning approach can predict lactate trends from non-invasive parameters of patients with sepsis. This retrospective study analyzed adult sepsis patients in the Medical Information Mart for Intensive Care IV (MIMIC-IV) dataset. Inclusion criteria were two or more lactate tests within 6 h of diagnosis, an ICU stay of at least 24 h, and a change of ≥1 mmol/liter in lactate level. Naïve 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 performed worse than the other methods when predicting constant trend. LMT algorithm with four features (heart rate, oxygen saturation, initial lactate, and time interval variables) achieved 0.80 in terms of AUC (AUPRC = 0.921). We can say that machine learning models that employ logistic regression architectures, i.e., LMT algorithm achieved good results in lactate trend prediction tasks, and it can be effectively used to assess the state of the patient, whether it is stable or improving.
A Hybrid Images Deep Trained Feature Extraction and Ensemble Learning Models for Classification of Multi Disease in Fundus Images
Authors: Verma Jyoti , Kansal Isha , Popli Renu , Khullar Vikas , Singh Daljeet , Snehi Manish , Kumar Rajeev 
Published: May 2024

AbstractRetinal disorders, including diabetic retinopathy and macular degeneration due to aging, can lead to preventable blindness in diabetics. Vision loss caused by diseases that affect the retinal fundus cannot be reversed if not diagnosed and treated on time. This paper employs deep-learned feature extraction with ensemble learning models to improve the multi-disease classification of fundus images. This research presents a novel approach to the multi-classification of fundus images, utilizing deep-learned feature extraction techniques and ensemble learning to diagnose retinal disorders and diagnosing eye illnesses involving feature extraction, classification, and preprocessing of fundus images. The study involves analysis of deep learning and implementation of image processing. The ensemble learning classifiers have used retinal photos to increase the classification accuracy. The results demonstrate improved accuracy in diagnosing retinal disorders using DL feature extraction and ensemble learning models. The study achieved an overall accuracy of 87.2%, which is a significant improvement over the previous study. The deep learning models utilized in the study, including NASNetMobile, InceptionResNetV4, VGG16, and Xception, were effective in extracting relevant features from the Fundus images. The average F1-score for Extra Tree was 99%, while for Histogram Gradient Boosting and Random Forest, it was 98.8% and 98.4%, respectively. The results show that all three algorithms are suitable for the classification task. The combination of DenseNet feature extraction technique and RF, ET, and HG classifiers outperforms other techniques and classifiers. This indicates that using DenseNet for feature extraction can effectively enhance the performance of classifiers in the task of image classification.
Exploring and Extending Human-Centered Design to Develop AI-Enabled Wellbeing Technology in Healthcare
Authors: Tahvanainen Laura , Tetri Birgitta , Ahonen Outi 
Published: May 2024

AbstractDigital transformation and digitalisation are rapidly affecting the society. The gradually increasing applications of different types of AI into solutions and services are welcome, but there are associated risks. These include, for example, within human aspects of care undermining fundamental rights, ethical considerations, sustainability, and policies and regulations. This change permeates every societal level, but it is especially evident in the healthcare sector due to the ageing population and shortage of professionals. This situation also places pressure on the development of competencies among healthcare professionals. A human-centered approach in design and design methods can promote the development of AI-based solutions in transdisciplinary and cross-disciplinary processes encompassing numerous stakeholders, scientific orientations, and perspectives. There is a need for research and evaluation of Human-Centered Design (HCD) processes and design methods to develop and gain more insights for future development.This study was conducted as research through design. It aimed to elucidate the application and insights gained from the adopted Service design process for AI-enabled services and HCD approach while developing AI-empowered solution, Voima-chatbot. One of this research's main conclusions and realization is the shift from purely HCD towards Life-Centered design of AI-enabled solutions with a human-in-the-loop. In addition, this project increased the understanding of the deep importance of having a transdisciplinary dialogue with developers during the process of developing digital well-being devices and combining different professional competencies to achieve the best working solutions.
Influencing Factors in Digital Health Intervention Uptake: The Interplay of Education, Lifestyle, and Digital Literacy
Authors: Ruotsalainen Ilona , Valtanen Mikko , Kärsämä Riikka , Umer Adil , Parikka Suvi , Lundqvist Annamari , Lindström Jaana 
Published: May 2024

AbstractChronic diseases strain global healthcare economically, and integrating digital solutions are proposed to help in meeting the rising demand. Digital health interventions (DHIs) offer promise for personalized, and cost-effective health services, however, factors influencing their uptake remain unclear. We examined whether the probability of lifestyle DHI uptake varies among individuals with different educational levels and lifestyles, based on their attitudes and usage of e-services. We also examined the effect of sex and age, and the association between DHI uptake and both educational attainment and overall lifestyle. A possibility to start using a web-based lifestyle DHI was offered to a subgroup (n = 6978) of Healthy Finland survey participants and adjusted logistic regression models were used to investigate the factors affecting uptake. We found that higher education and healthier lifestyle, as indicated by lifestyle score, were related to higher odds of DHI uptake. However, the effects of age, sex, independence of e-service use, and competence to use online services varied across lifestyle score groups. No significant interactions were observed related to educational attainment. These results imply that lifestyle DHIs are less likely to reach individuals with less-healthy lifestyle habits and lower educational attainment. In addition, some predictors affected the uptake differently across lifestyle score groups, suggesting that implementations of DHIs might attempt strategies to optimize the participation rates in especially targeted subgroups.