bluuebunny/crossref_metadata_2025 huggingface dataset:
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Authors: Ni Zhang  , Zhao Jing-bo  , Fan Xin
Published: February 2025

Distributed drive electric vehicle steering system affect the vehicle handling stability, active safety and ride comfort and other performance. Electric power steering (EPS) is a new vehicle power steering technology, in line with the automotive energy conservation, environmental development theme, consistent with the theme of the development of automotive electronics, intelligent vehicles, and become the focus of attention for domestic and foreign auto industry experts and scholars. The dynamic model of EPS is established, and the influence of the perturbation of parameters such as parameter perturbation, sensor measurement noise and external disturbance in the dynamic model of electric power steering control system is analyzed by using H∞control theory. In the process of solving controller, the weight function modeling and linear fractional transformation theory deals with these uncertainties and designs the H∞controller of the steering assist process. The performance of the controller is simulated by Matlab. The simulation results show that the controller has good robust stability and robust performance.
Research on Wireless Mesh Network's Application of Position Information Sharing Service
Authors: Xu Xiao-tao  , Guo Cai-wang  , Wang Shi
Published: February 2025

Wireless Mesh Network is a new kind of wireless communication technology widely used in near-field communication, has obvious application advantage in position information sharing service. The paper introduce WMN's technical characteristics used in the fields of Wireless Personal Area Network, analyze WMN's application advantage compared with Ad hoc Network, discuss four kinds of WPAN's traditional application mechanism based on WMN. Based above, describe a new kind of WPAN standard based on WMN called IEEE 802.15.5. Then, put forward a WMN's application case used in vehicle navigation and positioning, has important practical guiding significance of instructing WMN used in the fields of position information sharing service.
Design and Development of Chongqing Traffic Weather Service System Based on WebGIS
Authors: Han Shigang  , Xia Baicheng  , Min Fanhua
Published: February 2025

To satisfy the weather service requirements of Chongqing traffic departments, this paper designed the traffic weather service system of Chongqing (TWSSC) based on WebGIS by using B/S technology and taking the advantage of the client technology. TWSSC integrates highway information, highway meteorological observing data and forecasting and early warning service information, and apply such technology as tile map, Skyline 3D map and road weather inversion technique. TWSSC has functions of querying Chongqing highway information, monitoring weather conditions in real time, issuing early warning information, and visualizing meteorological service data and products.
Modified Cuckoo Search Based Neural Networks for Forest Types Classification
Authors: Chatterjee Sankhadeep  , Dey Nilanjan  , Sen Soumya  , Ashour Amira S.  , Fong Simon James  , Shi Fuqian
Published: February 2025

Pixel classification in land scape images is a challenging process especially in forest images due to the similar spectral features of pixels situated close to each other. Previously, meta-heuristic coupled artificial neural network (ANN) models have been used to classify the two-different species, namely Japanese Cedar, Japanese Cypress and one mixed forest class. Previous attempts have shown reasonable improvement in the classification process using genetic algorithm (GA) supported neural network over other traditional approaches. Consequently, in the current work, a modified Cuckoo Search (CS) supported Neural Network (NN-MCS) classifier is proposed. The lévy flight associated with cuckoo search has been modified using McCulloch's method of generating stable random numbers. The proposed approach is compared with GA-NN using single objective function and CS-NN (ANN trained with CS) classifiers in terms of confusion matrix based performance metrics. The results depicted the dominance of the suggested NN-MCS model compared to the CS-NN model to a greater extent.
Health Literary and the Arts: Exploring the Intersection
Authors: Ike John D.  , Parker Ruth M.  , Logan Robert A.
Published: February 2025

Historically, study and implementation of health literacy mostly focused on text-based information with frequent attention to medical and health related content within an increasingly complex healthcare system. This chapter introduces visual literacy, particularly as it relates to the visual arts, as a potentially understudied and underutilized component of health literacy that might offer benefit to both patients and healthcare workers. Literacy is both content and context specific. We posit that interaction with the arts improves the ability to appreciate the context inherent within communication across cultures and belief systems.
Seeking an Expanded, Multidimensional Conceptual Approach to Health Literacy and Health Disparities Research
Authors: Logan Robert A.
Published: February 2025

This chapter compares the conceptual foundations of health literacy and health disparities. It details some of the conceptual differences between health literacy and health disparities and explains some similarities that suggest the need for increased research collaboration. The chapter is among the first to address the structural and social determinants of health together and explain that future research needs to assess their interactions.
Alarm Fatigue vs User Expectations Regarding Context-Aware Alarm Handling in Hospital Environments Using CallMeSmart
Authors: Solvoll Terje  , Arntsen Harald  , Hartvigsen Gunnar
Published: February 2025

Surveys and research show that mobile communication systems in hospital settings are old and cause frequent interruptions. In the quest to remedy this, an Android based communication system called CallMeSmart tries to encapsulate most of the frequent communication into one hand held device focusing on reducing interruptions and at the same time make the workday easier for healthcare workers. The objective of CallMeSmart is to use context-awareness techniques to automatically monitor the availability of physicians' and nurses', and use this information to prevent or route phone calls, text messages, pages and alarms that would otherwise compromise patient care. In this paper, we present the results from interviewing nurses on alarm fatigue and their expectations regarding context-aware alarm handling using CallMeSmart.
Secondary Use of EHR: Interpreting Clinician Inter-Rater Reliability Through Qualitative Assessment
Authors: Mullin Sarah  , Anand Edwin  , Sinha Shyamashree  , Song Buer  , Zhao Jane  , Elkin Peter L.
Published: February 2025

In a retrospective secondary-use EHR study identifying a cohort of Non-Valvular Atrial Fibrillation (NVAF) patients, chart abstraction was done by two sets of clinicians to create a gold standard for risk measures CHA2DS2-VASc and HAS-BLED. Inter-rater reliability between each set of clinicians for NVAF and the outcomes of interest were variable, ranging from extremely low agreement to high agreement. To assess the chart abstraction process, a focus group and a survey was conducted. Survey findings revealed patterns of difficulty in assessing certain items dealing with temporality and social data. The focus group raised issues on the quality and completeness of EHR data, including missing encounters, truncated notes, and low granularity. It also raised the issue of the usability of the data system, the Clinical Data Viewer, which did not mirror a live EHR and made it difficult to record outcomes. Finally, the focus group found it was difficult to infer certain outcomes, like severity, from the provided data. These factors produced differences in clinician rated outcomes.
Health Sciences Library Closings; A Context Sensitive Pilot Study
Authors: Schwartz Diane G.  , Elkin Peter L.
Published: February 2025

A significant number of U.S. health sciences libraries have closed since the mid-1990's. A pilot study was conducted with academic physicians to understand the impact of closing the health sciences library in the teaching hospital with which they were affiliated. A brief survey was designed and distributed to fourteen faculty members with thirteen useable responses received. The study elicited a context-sensitive perspective on the closing of the library with the most noteworthy outcome being the additional time required by attending physicians and trainees to perform the work that previously was performed by library staff. The loss of the expert literature search, instructional services, journal request, and interlibrary loan services had the most significant impact on study participants. Further research is needed to understand the long term consequences of closing hospital-based health sciences library on the education of physicians.
How Can Health Information Technologies Contribute to Improve Health Care Services for High-Need Patients?
Authors: Nøhr Christian  , Botin Lars  , Zhu Xinxin
Published: February 2025

This paper discusses how health information technologies like tele-care, tele-health and tele-medicine can improve the condition for high-need patients, specifically in relation to access. The paper addresses specifically the values of timeliness and equity and how tele technological solutions can support and enhance these values. The paper introduces to the concept of scaffolding, which constitutes the framework for dynamic, appropriate, caring and embracing approaches for engaging and involving high-need patients that are vulnerable and exposed. A number of specific considerations for designing tele-technologies for high-need patients are derived, and the paper concludes that ethical and epistemological criterions for design are needed in order to meet the needs and requirements of the weak and exposed.
Exploring Socio-Technical Insights for Safe Nursing Handover
Authors: Wong Ming Chao  , Yee Kwang Chien  , Turner Paul
Published: February 2025

Current efforts to improve nursing handover frequently use prescriptive approaches based on research evidence of handover issues within a single nursing ward or nursing specialty. Despite reported handover improvement, few studies adequately consider the transferability of results to other nursing handover environments or acknowledge the unique attributes that supported sustained improvement. With the increasing diffusion of electronic tools it has become even more critical to ensure that socio-technical issues that may impact on the quality and safety of nursing handovers are identified. This paper describes a qualitative research project that examined nursing handover in three different wards – General Medicine, General Surgery and Department of Emergency Medicine in a tertiary teaching hospital. Through conduct of a detailed analysis of nursing handover processes, this paper highlights the similarities and differences in the handover among the three different wards and presents five key socio-technical insights to support safe nursing handover.
Design Thinking for mHealth Application Co-Design to Support Heart Failure Self-Management
Authors: Woods Leanna  , Cummings Elizabeth  , Duff Jed  , Walker Kim
Published: February 2025

Heart failure is a prevalent, progressive chronic disease costing in excess of $1billion per year in Australia alone. Disease self-management has positive implications for the patient and decreases healthcare usage. However, adherence to recommended guidelines is challenging and existing literature reports sub-optimal adherence. mHealth applications in chronic disease education have the potential to facilitate patient enablement for disease self-management. To the best of our knowledge no heart failure self-management application is available for safe use by our patients. In this paper, we present the process established to co-design a mHealth application in support of heart-failure self-management. For this development, an interdisciplinary team systematically proceeds through the phases of Stanford University's Design Thinking process; empathise, define, ideate, prototype and test with a user-centred philosophy. Using this clinician-led heart failure app research as a case study, we describe a sequence of procedures to engage with local patients, carers, software developers, eHealth experts and clinical colleagues to foster rigorously developed and locally relevant patient-facing mHealth solutions. Importantly, patients are engaged in each stage with ethnographic interviews, a series of workshops and multiple re-design iterations.
Adoption and Use of a Mobile System at Home Care
Authors: Vasalampi Annika
Published: February 2025

This research concerns mobile system adoption and use among home care nurses at one home care organization in Finland. The aim was to get insights on somewhat poor adoption and utilization of a mobile system they use. 12 nurses were interviewed and observed at home visit to gain insights on how the system could better facilitate their work routines. A requirement analysis was produced based on the results and is to be discussed with the management of the organization and the service provider.
Using the Assistance on Demand Platform to Set Up a Network of Assistance Services
Authors: Leligou Helen C.  , Panagiotis Athanasoulis  , Tsakou Gianna  , Vanderheiden Gregg  , Kocsis Otilia  , Katevas Nikos
Published: February 2025

The Assistance on Demand (AoD) platform is a novel open-source infrastructure which enables the set-up and web publication of assistance services. This paper focuses on the potential of the AoD functionality to enable the configuration and creation of a Network of Assistance Services (NAS) by non-expert users (e.g. consumers, family members).
Mobile Delivery of Health Information for People with Mild Cognitive Impairment
Authors: Lloyd Gareth  , Munro Susan D.  , Arnott John L.
Published: February 2025

The design of a smartphone application (app) for promoting healthy lifestyle choices has been investigated for people with mild cognitive impairment. The app was designed to provide health-related messages and assist users to keep track of activities such as walking, eating and drinking water. A reward scheme with gold, silver and bronze awards was incorporated as a means of assisting user motivation. Responses to the app and user feedback were gathered for purposes of evaluation and improvement. Outcomes indicate that the approach has some potential and could have good implications for encouraging positive health-related behaviour change in this population, hence prompting further investigation and development of the concept.
Technology for Early Detection of Depression and Anxiety in Older People
Authors: Andrews Jacob A.  , Astell Arlene J.  , Brown Laura J.E.  , Harrison Robert F.  , Hawley Mark S.
Published: February 2025

Under-diagnosis of depression and anxiety is common in older adults. This project took a mixed methods approach to explore the application of machine learning and technology for early detection of these conditions. Mood measures collected with digital technologies were used to predict depression and anxiety status according to the Geriatric Depression Scale (GDS) and the Hospital Anxiety and Depression Scale (HADS). Interactive group activities and interviews were used to explore views of older adults and healthcare professionals on this approach respectively. The results show good potential for using a machine learning approach with mood data to predict later depression, though prospective results are preliminary. Qualitative findings highlight motivators and barriers to use of mental health technologies, as well as usability issues. If consideration is given to these issues, this approach could allow alerts to be provided to healthcare staff to draw attention to service users who may go on to experience depression.
Conjuring up New Technology – Using Magic Objects in Co-Ideation with Stroke Survivors
Authors: Rassmus-Gröhn Kirsten  , Magnusson Charlotte  , Rydeman Bitte  , Randall Gary  , Belson Sarah
Published: February 2025

Ideation means to generate ideas, and when involving non-designers in these activities they need to be informed about the scope of the possibilities without limiting their imagination. This is a general challenge, which becomes particularly important when it comes to advanced technology ideation together with participants that may not have in-depth knowledge of technological designs and solutions. In this study, we supported the ideation process by presenting a kit of magic objects (consisting of cards and physical props) to stroke survivors participating in a co-design workshop carried out within the STARR EU project. The kit was seen to generally work well, but improvements are suggested for the introduction, the design of the cards and the number of objects used.
Development/Testing of a Monitoring System Assisting MCI Patients: The European Project INLIFE
Authors: Kaimakamis Evangelos  , Karavidopoulou Vaia  , Kilintzis Vassilios  , Stefanopoulos Leandros  , Papageorgiou Valentini
Published: February 2025

INLIFE is a project cofounded from the European Union aiming in prolonging independent living of elderly people with cognitive impairment based on open, seamless ICT services supporting communication, daily activities, providing health services and professional care to the elderly. The main innovation stems from ICT solutions offering 19 different services adapted on specific characteristics elderly people with mild cognitive impairment, early and later stages of Dementia, cognitive impairment and co-morbid condition, as well as their formal and informal caregivers.
ICT Services for Life Improvement for the Elderly
Authors: Sánchez-Rico Alejandro  , Garel Pascal  , Notarangelo Isabella  , Quintana Marcos  , Hernández Gustavo  , Asteriadis Stylianos  , Popa Mirela  , Vretos Nicholas  , Solachidis Vassilis  , Burgos Marta  , Girault Ariane
Published: February 2025

Integrated care ICT Platform to support patients, care-givers and health/social professionals in the care of dementia and Parkinson's disease with training, empowerment, sensor-based data analysis and cooperation services based on user-friendly interfaces.
The Use of Apps for Health in Persons with Multiple Sclerosis, Parkinson's Disease and Stroke – Barriers and Facilitators
Authors: Winberg C.  , Kylberg M.  , Pettersson C.  , Harnett T.  , Hedvall P.-O.  , Mattsson T.  , Månsson Lexell E.
Published: February 2025

Introduction: The importance of mobile health has increased during recent years but few studies have described the use of apps among persons with neurological disabilities.
A Self-Assessment Framework for Inclusive Schools Supporting Assistive Technology Users
Authors: Hoogerwerf Evert-Jan  , Solander-Gross Andrea  , Mavrou Katerina  , Traina Ivan  , Hersh Marion
Published: February 2025

In order to support schools to assess their performance in supporting children with disabilities in their ICT and ICT-AT needs, a self-assessment framework was developed by a task force of partners and associate partners of the ENTELIS project. The self-assessment tool aims to help educational establishments that welcome learners with disabilities to assess their current outcomes and to plan improvements in supporting these students in increasing digital literacy and developing digital skills. This includes the use of mainstream Information and Communication Technology (ICT) and specially designed digital Assistive Technologies (ICT-AT). This can only successfully happen if schools fully embrace an inclusive approach to education. In this paper the authors describe the development of the framework and the further steps for its use.
Auditing the Accessibility of Massive Open Online Courses (MOOCs)
Authors: Iniesto Francisco  , McAndrew Patrick  , Minocha Shailey  , Coughlan Tim
Published: February 2025

The outcome from the research being reported in this paper is the design of an accessibility audit to evaluate Massive Open Online Courses (MOOCs) for accessibility and to arrive at solutions and adaptations that can meet user needs. This accessibility audit includes expert-based heuristic evaluations and user-based evaluations of the MOOC platforms and individual courses.
Towards a Cognitive Screenreader
Authors: Heumader Peter  , Miesenberger Klaus  , Koutny Reinhard
Published: February 2025

This paper describes the current state of development of a tool that assists people with cognitive disabilities while using the internet. The support is provided by interfaces that give additional or alternative information for content or user interaction mechanics that are not understood by the support.
mBalance: An Intelligent Android Application to Assess and Analyze Body Balance
Authors: Moral-Munoz Jose A.  , Toscano Adan  , Cobo Manuel J.  , Perez Ignacio J.
Published: February 2025

Body balance is related to different pathologies and its improvement has been shown to help with injuries' recovery and prevention. There are several methods to assess the body balance in a clinical environment, and their quickness and reliability are becoming important. However, traditional procedures have some limitations or disadvantages. Thus, the use of mHealth technologies is considered here to perform the body balance assessment in a reliable and within everyone's reach way. This work presents mBalance, a mHealth system to assess body balance by using a mobile device and a BOSU ball. The mobile accelerometer register the movement and the information is processed and managed to determine the subject's body balance level. In order to show the interest on the mBalance system, the System Usability Scale was used to know the expert opinions.
Computational Visualization of Customer Mood Using Affective Space Model Approach
Authors: Kamaruddin Norhaslinda  , Handayani Dini  , Wahab Abdul
Published: February 2025

Customers' mood information is acquired to facilitate marketers' understanding in order to tailor the marketing strategies for positive outcomes optimization. Mood can be reasonably hypothesized as one of the factor that influences customers' decision in buying the products or services offered. There have been many researchers reporting the correlation between moods and buying decision. However, to date, there is no such method that can exactly quantify the customer's mood. Typically, a questionnaire is given to the participant to gauge their mood on the focused product or services. The drawback from such approach is that participants can fake, exaggerate or suppress their mood resulting to questionable inference. Hence, a new method of data acquisition is needed to be able to visualize the dynamics of the customers' mood for more accurate analysis. In this paper, the customer brain signal is captured using electroencephalogram (EEG) to track and record brain wave patterns in regard to their emotional states. The sequence of emotion is then used to identify their mood. A computational visualization technique is adopted to facilitate understanding of one minute emotion transition that assembling mood. The experimental results show that such approach is feasible and can be extended to study mood in a more comprehensive manner. It is envisaged that this work will be the catalyst for large mood data analysis tool that can help researchers in the near future to look at mood and buying decision for the improvement of comprehensive customer understanding in a more accurate manner
Leveraging Test Case Generation in the Testing Process – An Integration of Human Oracles with Derived Oracles
Authors: Von Hof Vincent
Published: February 2025

In the testing process humans examine the behavior of an application under test to determine what would constitute a failure. By specifying—for a given input and result—whether or not this combination leads to desired behavior, they essentially constitute to what is called the test oracle. To automate oracle generation, techniques were introduced to derive the oracle from models, specification, or by reusing artifacts. In the end, to complete the oracle, a human must be involved. Automated Test Case Generation (ATCG) on the other hand, already derives all feasible test cases from the program itself - baring judgment about which cases correspond to faults. This paper introduces a tool that derives the oracle by using ATCG as input for a human oracle. By combining ATCG with human oracles, we aim to reduce costs associated with the testing process.
A Holistic Domain Knowledge Discovery and Recommendation System for Collaborative Wikis
Authors: Bernabé-Moreno Juan  , Tejeda-Lorente Álvaro  , Porcel Carlos  , Herrera-Viedma Enrique
Published: February 2025

Wikipedia is the best-developed attempt so far to gather all human knowledge in one place yet there's no approach to exhaustively address all different types of information requirements. In this work we propose an information discovery, retrieval and recommendation system supported by an ensemble of techniques to cover all informational needs in a holistic and dynamic way. We first introduce the typology of informational needs and then present the system building blocks, explaining the ensemble of supporting techniques and which particular information requirement type benefits from each one. To prove how our system works, we discuss the results of the Machine Learning semantic field.
A Survey on Applying Machine Learning Techniques for Behavioral Awareness
Authors: Preuveneers Davy  , Ramakrishnan Arun  , Van Hamme Tim  , Rimmer Vera  , Berbers Yolande  , Joosen Wouter
Published: February 2025

This survey reviews the state-of-the-art on the applicability of machine learning techniques for behavioral awareness. Not only is behavioral awareness an important capability of ambient assisted living environments to better support individuals during their activities of daily living, it is also gaining attention as a way to identify individuals based on distinguishing or unique features in their behavior. In this work, we not only pay attention to individual behavior but also to behavioral traits of a group of individuals as a whole. This survey documents a broad overview of the state-of-the-art in behavioral recognition, learning and mining. It provides an overview of how activities can be recognized through the identification and classification of certain features in event-based data streams. This overview highlights a variety of well-known probabilistic learning and prediction methods and how they have been applied for the purpose of identification and activity recognition.
EKRUCAmI Architecture – Applications in Healthcare Domain
Authors: Ramos Carlos  , Martinho Diogo  , Marreiros Goreti  , Villarrubia Gabriel  , De Paz Juan F.  , Corchado Juan M.  , Ko Hoon  , Kim Haeng-kon  , Yoe Hyun
Published: February 2025

Ambient Intelligence is a paradigm in Artificial Intelligence which promotes intelligent computing and responds to the necessities of every person in many different environments whether it is a home, classroom, a shopping, or a hospital. Nowadays we are increasingly seeing and talking about issues such as aging populations or the increase in the number of patients with chronic diseases (among other issues). Looking at the solutions available in this area it is necessary to develop more effective systems that can support people and improve their quality of life. This work is a brief study on EKRUCAmI architecture and its suitability to the healthcare sector. Some healthcare systems will be presented which have been designed to use EKRUCAmI architecture.
Multivariate Regression with Incremental Learning of Gaussian Mixture Models
Authors: Acevedo-Valle Juan M.  , Trejo Karla  , Angulo Cecilio
Published: February 2025

Within the machine learning framework, incremental learning of multivariate spaces is of special interest for on-line applications. In this work, the regression problem for multivariate systems is solved by implementing an efficient probabilistic incremental algorithm. It allows learning high-dimensional redundant non-linear maps by the cumulative acquisition of data from input-output systems. The proposed model is aimed at solving prediction and inference problems. The implementation introduced in this work allows learning from data batches without the need of keeping them in memory afterwards. The learning architecture is built using Incremental Gaussian Mixture Models. The Expectation-Maximization algorithm and general geometric properties of Gaussian distributions are used to train the models. Our current implementation can produce accurate results fitting models in real multivariate systems. Results are shown from testing the algorithm for both situations, one where the incremental learning is demonstrated and the second where the performance to solve the regression problem is evaluated on a toy example.
MFCC vs. MPEG-7 Frame Description for Anuran Sound Classification
Authors: Luque Amalia  , Gómez-Bellido Jesús  , Carrasco Alejandro  , Falomir Zoe  , González-Abril Luis
Published: February 2025

Several authors have shown that the sounds of anurans can be used as an indicator of climate change. For this purpose anuran sound automatic classification has become an important issue for biologists and other climate scientists. In this paper two approaches have been used to feature every sound frame: Mel Frequency Cepstral Coefficients (MFCC); and parameters based on the MPEG-7 standard. The methods to extract the features and to classify the sounds are described. Up to ten different classification algorithms have also been considered. Their results are compared using several metrics, mainly based on the classification error rate. The main conclusion is that both, the MFCC and the MPEG-7 parameters, are adequate for featuring and classifying anuran sounds, although MFCC get best metrics for more classifiers. When the number of parameters is an important concern, MPEG-7 features show better results. Additionally, from a qualitative point of view, MPEG-7 features are semantically richer than their MFCC counterparts.
On Dynamical Systems for Sensorimotor Contingencies. A First Approach from Control Engineering
Authors: Angulo Cecilio  , Acevedo-Valle Juan M.
Published: February 2025

According to the sensorimotor approach, cognition is constituted by regularities in the perceptual experiences of an active and situated agent. This perspective rejects traditional inner representational models, stressing instead patterns of sensorimotor dependencies. Those relations are called sensorimotor contingencies (SMC). Many research areas and accounts are working on and related with it. In particular, four distinct kinds of SMCs have been previously introduced for environment, habitat, coordination and strategy using dynamical models from a psychological perspective. As dynamical systems, in this paper we analyze SMCs, for the very first time, from a modern control engineering perspective. We provide equations and block diagrams translating the psychological proposal to control engineering. We also analyze the original toy example proposed from the psychological domain into the modern control engineering point of view, as well as we propose a first approach to this toy example coming from the control engineering domain.
Standards-Based Procedural Phenotyping: The Arden Syntax on i2b2
Authors: Mate Sebastian  , Castellanos Ixchel  , Ganslandt Thomas  , Prokosch Hans-Ulrich  , Kraus Stefan
Published: February 2025

Phenotyping, or the identification of patient cohorts, is a recurring challenge in medical informatics. While there are open source tools such as i2b2 that address this problem by providing user-friendly querying interfaces, these platforms lack semantic expressiveness to model complex phenotyping algorithms. The Arden Syntax provides procedural programming language construct, designed specifically for medical decision support and knowledge transfer. In this work, we investigate how language constructs of the Arden Syntax can be used for generic phenotyping. We implemented a prototypical tool to integrate i2b2 with an open source Arden execution environment. To demonstrate the applicability of our approach, we used the tool together with an Arden-based phenotyping algorithm to derive statistics about ICU-acquired hypernatremia. Finally, we discuss how the combination of i2b2's user-friendly cohort pre-selection and Arden's procedural expressiveness could benefit phenotyping.
DisEpi: Compact Visualization as a Tool for Applied Epidemiological Research
Authors: Benis Arriel  , Hoshen Moshe
Published: February 2025

Outcomes research and evidence-based medical practice is being positively impacted by proliferation of healthcare databases. Modern epidemiologic studies require complex data comprehension. A new tool, DisEpi, facilitates visual exploration of epidemiological data supporting Public Health Knowledge Discovery. It provides domain-experts a compact visualization of information at the population level. In this study, DisEpi is applied to Attention-Deficit/Hyperactivity Disorder (ADHD) patients within Clalit Health Services, analyzing the socio-demographic and ADHD filled prescription data between 2006 and 2016 of 1,605,800 children aged 6 to 17 years. DisEpi's goals facilitate the identification of (1) Links between attributes and/or events, (2) Changes in these relationships over time, and (3) Clusters of population attributes for similar trends. DisEpi combines hierarchical clustering graphics and a heatmap where color shades reflect disease time-trends. In the ADHD context, DisEpi allowed the domain-expert to visually analyze a snapshot summary of data mining results. Accordingly, the domain-expert was able to efficiently identify that: (1) Relatively younger children and particularly youngest children in class are treated more often, (2) Medication incidence increased between 2006 and 2011 but then stabilized, and (3) Progression rates of medication incidence is different for each of the 3 main discovered clusters (aka: profiles) of treated children. DisEpi delivered results similar to those previously published which used classical statistical approaches. DisEpi requires minimal preparation and fewer iterations, generating results in a user-friendly format for the domain-expert. DisEpi will be wrapped as a package containing the end-to-end discovery process. Optionally, it may provide automated annotation using calendar events (such as policy changes or media interests), which can improve discovery efficiency, interpretation, and policy implementation.
Observation Error Handling Methods for Data Assimilation Coupled with Fuzzy Control Algorithms
Authors: Bai Yulong  , Lu Yongnan  , Guo Pengfei  , Ma Yongjie  , Ma Boyang
Published: February 2025

In data assimilation for numerical weather prediction, observation errors are typically neglected or are assumed to have zero correlations, resulting in a loss of information. For spurious correlations in data assimilations of limited ensemble sizes, a new method is proposed by calculating observation distances and constructing equivalent observation position weights. Coupled with standard fuzzy control algorithms, a fuzzy control ensemble transform Kalman filter (FETKF) is presented, and the corresponding procedures are given. Within the framework of the classical Lorenz-96 chaotic model, we compare the performance of the ensemble transform Kalman filter (ETKF), the local ensemble transform Kalman filter (LETKF), and the proposed FETKF with varying physical parameters. Comparisons are drawn between the LETKF localization coefficients and FETKF spatial distance vectors to calculate the corresponding weight function of the chaotic model. The results show that the new method can eliminate spurious correlations, prevent long-range observation effects of state update variables and reduce analysis errors. The error handling methods based on fuzzy control performed well under both perfect and imperfect model scenarios in the Lorenz-96 model.
Similarity Measures Using Fuzzified Ratings for Collaborative Filtering
Authors: Lee Soojung
Published: February 2025

Collaborative filtering-based recommender systems have been popular for Internet users as they are helpful in searching for useful information promptly. These systems rely on similarity measures to obtain recommendations from other users based on their rating history. This paper addresses the problem of vagueness and subjectivity in user ratings. To relieve this problem, we adopt the fuzzy logic to transform ratings and then compute similarity using the fuzzified ratings. Performance of the proposed method is investigated to find that it significantly outperforms existing similarity measures using hard user ratings in terms of prediction accuracy, especially with a sparse and short-ranged dataset.
Research on Financial Risk Monitoring Index of High-Tech Enterprises–Based on Entropy-Fuzzy Comprehensive Evaluation
Authors: Yang Liu  , Zhang Youtang
Published: February 2025

As China's economic growth rate slows down, the impetus of our economic growth gradually transforms from investment to innovation. Based on the Enterprise Performance Evaluation Standard Value which is released by SASAC, this thesis constructs the financial risk monitoring index model of high-tech enterprise, with the adoption of entropy-fuzzy comprehensive evaluation. Moreover, it provides reference for the risk monitoring of high-tech enterprises and investors' investment decisions by utilizing the data of computer services and software companies from 2013 to 2015 in Shanghai and Shenzhen for empirical testing.
S-Fiber Probe for Refraction Index Sensing
Authors: Yang Xian-hui  , Yang Rui  , Gao Shuo  , Gu Xue-mei  , Yu Bo-tao  , Zhang Shi-chuan
Published: February 2025

A refractive index (RI) sensor which based on an S-tapered fiber probe (STFP) with a silver mirror on its end facet is demonstrated. The fiber probe has a compact size of about 1 mm, making it proper for sensing in narrow or limited space. It is stiff to bend due to the short probe structure, leading to avoid the cross-sensitivity of bending. The reflection spectra of the STFPs with different structure length have been analyzed and simulated. A proper structure length will result in narrow dips and peaks, which can be used to enhance the measurement accuracy. Its refractive index sensitivity which is normally in the range of 1.332~1.387 reaches 268.8 nm/RI unit, which is 9 times higher than that of the existing reflective fiber-taper-based RI sensor. Furthermore, the thermal response experimental results show that the STFP is temperature insensitive.
Accessing Reliable Health Information on the Web: A Review of the HON Approach
Authors: Boyer Célia  , Gaudinat Arnaud  , Hanbury Allan  , Appel Ron D.  , Ball Marion J.  , Carpentier Michel  , van Bemmel Jan H.  , Bergmans Jean-Paul  , Hochstrasser Denis  , Lindberg Donald  , Miller Randolph  , Peterschmitt Jean-Claude  , Safran Charles  , Thonnet Michèle  , Geissbühler Antoine
Published: February 2025

Accessing online health content of high quality and reliability presents challenges. Laypersons cannot easily differentiate trustworthy content from misinformed or manipulated content. This article describes complementary approaches for members of the general public and health professionals to find trustworthy content with as little bias as possible. These include the Khresmoi health search engine (K4E), the Health On the Net Code of Conduct (HONcode) and health trust indicator Web browser extensions.
Predicting Length of Stay for Obstetric Patients via Electronic Medical Records
Authors: Gao Cheng  , Kho Abel N.  , Ivory Catherine  , Osmundson Sarah  , Malin Bradley A.  , Chen You
Published: February 2025

Obstetric care refers to the care provided to patients during ante-, intra-, and postpartum periods. Predicting length of stay (LOS) for these patients during their hospitalizations can assist healthcare organizations in allocating hospital resources more effectively and efficiently, ultimately improving maternal care quality and reducing costs to patients. In this paper, we investigate the extent to which LOS can be forecast from a patient's medical history. We introduce a machine learning framework to incorporate a patient's prior conditions (e.g., diagnostic codes) as features in a predictive model for LOS. We evaluate the framework with three years of historical billing data from the electronic medical records of 9188 obstetric patients in a large academic medical center. The results indicate that our framework achieved an average accuracy of 49.3%, which is higher than the baseline accuracy 37.7% (that relies solely on a patient's age). The most predictive features were found to have statistically significant discriminative ability. These features included billing codes for normal delivery (indicative of shorter stay) and antepartum hypertension (indicative of longer stay).
Characterizing Restorative Dental Treatments of Sjögren's Syndrome Patients Using Electronic Dental Records Data
Authors: Siddiqui Zasim  , Wang Yue  , Makkad Payal  , Thyvalikakath Thankam
Published: February 2025

Scant knowledge exists on the type of restorative treatments Sjögren's syndrome patients (SSP) receive in spite of their high dental disease burden due to hyposalivation. Increased adoption of electronic dental records (EDR) could help in leveraging information from these records to assess dental treatment outcomes in SSP. In this study, we evaluated the feasibility of using EDR to characterize the dental treatments SSP received and assess the longevity of implants in these patients. We identified 180 SSP in ten years of patients' data at the Indiana University School of Dentistry clinics. A total of 104 (57.77%) patients received restorative or endodontic treatments. Eleven patients received 23 implants with a survival rate of 87% at 40 months follow-up. We conclude that EDR data could be used for characterizing the treatments received by SSP and for assessing treatment outcomes.
Connecting PHRs and EHRs for a Sustainable National Health System
Authors: Hovenga Evelyn  , Grain Heather
Published: February 2025

An EHR for integrated care (IEHR) is defined by the International Organization for Standardization (ISO) [1]: “…a repository of information regarding the health status of a subject of care, in computer processable form, stored and transmitted securely, and accessible by multiple authorised users, having a standardized or commonly agreed logical information model that is independent of EHR systems and whose primary purpose is the support of continuing, efficient and quality integrated health care. It contains information which is retrospective, concurrent and prospective.” We need to differentiate between EMR/EHR and the lifelong PHR in terms of type of data storage, sharing and use [2–3].
Comparing Cancer Information Needs for Consumers in the US and China
Authors: Ji Zongcheng  , Zhang Yaoyun  , Xu Jun  , Chen Xiaoling  , Wu Yonghui  , Xu Hua
Published: February 2025

Due to the differences in environments and cultures, consumers seeking cancer information in various regions of the world may have diverse needs. This study compares the cancer information needs for consumers in the US and China. Specifically, we first collected 1,000 cancer-related questions from Yahoo! Answers and Baidu Zhidao, respectively. Then, we developed a taxonomy of health information needs and manually classified the questions using the taxonomy. Finally, we analyzed the characteristics of information needs from consumers in both countries and summarized the differences between them. Our study demonstrated that although there are some common needs between consumers in the US and China, there are several significant differences between the two countries: the Chinese consumers are more likely to seek diagnosis and treatment online, while the US consumers prefer to seek common medical knowledge online.
Effects of e-Learning and m-Learning on Nursing Care in a Continuing Education Context: An Overview of Mixed Method Systematic Reviews (Protocol)
Authors: Rouleau Geneviève  , Gagnon Marie-Pierre  , Côté José  , Hudson Emilie  , Payne-Gagnon Julie  , Bouix-Picasso Julien  , Duboi Carl-Ardy
Published: February 2025

Continuing education is an imperative for professional nursing. e-Learning is one modality to support education and it has been extensively examined in a nursing academic context. An overview of quantitative, qualitative, and mixed-method systematic reviews were conducted to draw a broad picture of the effects of e-Learning and m-Learning used by registered nurses in a continuing education context.
Development of Asian Non-Small Cell Lung Cancer Survival Prediction Model Using an Innovative Method of Bayesian Network
Authors: Yin Bincan  , Xin Shichao  , Zhao Yuhong
Published: February 2025

We constructed a novel prognostic model using an innovative method of Bayesian Network (BN) to predict Non-Small Cell Lung Cancer survival status within 5 years after operation in the Asian population. The proposed BN model could present the relationship between prognostic factors and showed the highest performance among other machine learning (ML) algorithms.
Digital Health Information Workforce Planning Through a National Census
Authors: Gray Kathleen  , Butler-Henderson Kerryn
Published: February 2025

This poster describes the rationale and method for the development of a minimum data set as the first step toward an Australian national health information workforce census. Critical importance is attached to open and inclusive models, and the early and extensive engagement of key stakeholders, to provide a solid base for broader research into this workforce.
Acceptance and Use of eHealth/mHealth Applications for Self-Management Among Cancer Survivors
Authors: Jiang Yun  , West Brady T.  , Barton Debra L.  , Harris Marcelline R.
Published: February 2025

Cancer survivors' acceptance and use of eHealth/mHealth applications for self-management can be unique and are not fully understood. We used data from the Health Information National Trends Survey 4 Cycle 4 to examine cancer survivors' acceptance and use of eHealth/mHea applications for key self-management processes, and conducted logistic regression and Rao-Scott design-adjusted Chi-square tests to assess bivariate associations between potential predictors and actual use. Potential factors were selected based on the Individual and Family Self-Management theory. High acceptance of eHealth applictions was identified, and adoption of mHealth was relatively low. Younger, higher educated, married, employed, and higher income survivors tended to use eHealth/mHealth applications for self-management. Survivors who were newly diagnosed or still on treatment were more likely to look for cancer information online or communicate with health providers electronically. BMI and rural residency were associated with use of mHealth apps to achieve a health-related goal and treatment decision-making.
Measuring User Satisfaction with Clinical Information Systems: What Really Matters?
Authors: Schaffer Jonathan L.  , Haddad Peter  , Wickramasinghe Nilmini
Published: February 2025

The healthcare industry is increasingly investing in information systems / Information technology to enhance patient outcomes and organizational performance. This study qualitatively investigates the relationship between the overall satisfaction and five key aspects of clinical information systems. The results show that intuitive, easy-to-use, and collaboration enabling systems are more likely to satisfy users. The level of technical support and training also play key roles in determining user satisfaction in the clinical domain.
In Vitro Comparative Study Between Conventional and Computer-Assisted Surgery Methods for Planning and Resection of Bone Sarcomas
Authors: Ritacco L.E.  , Aponte-Tinao L.A.  , Muscolo D.L.  , Ayerza M.A.  , Albergo I.  , Farfalli G.L.  , Risk M.  , Gonzalez Bernaldo de Quiros F.  , Milano F.E.
Published: February 2025

This poster aims to achieve an “in vitro” comparative study between three methods: 2D digital images planning and execution without navigation (freehand with ruler and caliper), 3D planning and execution without navigation (freehand with ruler and caliper) and 3D planning and execution guided with navigation. 3D planning and navigated procedures potentially improve sarcoma resection.