bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of Robotic Rollators and Walking Trolleys in Japan
Authors: Matsumoto Osamu
Published: February 2025

In Japan, several types of robotic rollators and walking trolleys have been developed with financial assistance from the Japanese government, and some of them have been commercialized in 2015 and 2016. In this paper, the specifications and features of these devices are presented. Moreover, the physically assistive effects of these devices in elderly users are verified and discussed using the results of fundamental function tests and verification experiments.
Digital Support for Persons with Cognitive Impairment
Authors: Andreassen M.  , Boman I.-L.  , Danielsson H.  , Hemmingsson H.
Published: February 2025

Cognitive impairment may cause difficulties in planning and initiating daily activities, as well as remembering to do what is scheduled. This study investigates the effectiveness of an interactive web-based mobile reminder calendar that sends text messages to the users mobile phone as support in everyday life, for persons with cognitive impairment due to neurological injury/diagnoses. The study has a randomised controlled trail design with data collection at baseline and at follow-up sessions after two and four months. Data collection started in August 2016 and continues until December 2017. The interactive web-based mobile reminder calendar may give the needed support to remind the person and thus increase the ability to perform activities and to be independence in everyday life. Preliminary results will be presented regarding what effect the interactive web-based mobile reminder calendar have for the participants performance of everyday life activities as well as perceived quality of life.
Investigating the Effect of Social Robot Embodiment
Authors: Whelan Sally  , Kouroupetroglou Christos  , Santorelli Adam  , Raciti Massimiliano  , Barrett Eva  , Casey Dympna
Published: February 2025

The experiment described in this paper is an early assessment to identify if the embodiment of a verbal and visual user interaction system in a robot is more effective in people with dementia than when using the same system in a simple laptop. This study provides input for the robot's design.
Care Robot ZORA in Dutch Nursing Homes; An Evaluation Study
Authors: Kort Helianthe  , Huisman Chantal
Published: February 2025

From May 2016 – November 2016 the use of the ZORA robot was investigated in 15 long-term care facilities for older people. The ZORA robot is built as a social robot and used for pleasure and entertainment or to stimulate physical activities of the residents.
Living Lab as an Agile Approach in Developing User-Friendly Welfare Technology
Authors: Holappa Niina  , Sirkka Andrew
Published: February 2025

This paper discusses living lab as a method of developing user-friendly welfare technology, and presents a qualitative evaluation research of how living lab tested technologies impacted on the life of healthcare customers and professionals over test periods.
ICT Inexperienced Elderlies: What Would Attract Elderlies to Use Items of Technology?
Authors: Koscher Andrea  , Dittenberger Sandra  , Stainer-Hochgatterer Andreas
Published: February 2025

This paper presents the findings of the first end-user research study with seniors who are not familiar with operating ICT devices, executed as part of the EU-Active and Assisted Living research project Kith & Kin. This project aims at developing an ICT device for these seniors by building on their needs and real capabilities, encouraging communication and fostering social inclusion.
A Review of Physical Activity Monitoring and Activity Trackers for Older Adults
Authors: Barton John  , O'Flynn Brendan  , Tedesco Salvatore
Published: February 2025

The objective assessment of physical activity levels through wearable inertial-based motion detectors for an automatic, continuous and long-term monitoring of people in free-living environments is a well-known research area in literature. However, their application to older adults can present particular constraints. This paper reviews the methods of measuring physical activity, adoption of wearable devices in older adults, describes and compares existing commercial products encompassing activity trackers tailored for older participants.
Not Just the Right to a Wheelchair but the Right Wheelchair – Improving Brazilian Wheelchair Service Delivery
Authors: Maximo Tulio  , Clift Laurence
Published: February 2025

This paper discusses the barriers encountered before and after the implementation of good practice in the delivery of wheelchair provision services in Belo Horizonte city, Brazil. The results demystify some participants' initial idea that using an assessment form might take significantly more time. Major barriers to implementation had regard to the assessment of pressure sores and a lack of wheelchair suppliers.
Servomotor Assistance in the Improvement of Manual Wheelchair Mobility
Authors: Lahr Gustavo Jose Giardini  , Medola Fausto Orsi  , Sandnes Frode Eika  , Elui Valeria Meirelles Carril  , Fortulan Carlos Alberto
Published: February 2025

This study reports the development of a servo-controlled power-assisted wheelchair, designed to reduce the loads on the upper limbs while maintaining the drivability of a manual chair. It is presented the concept and implementation of an assisted propulsion system, focusing on the assistance controlling and the torque transmission.
How Accessible is Weibo for People with Visual Impairments?
Authors: Liu Zhifeng  , Chen Weiqin
Published: February 2025

Weibo is one of the most popular Chinese social media services. The literature has shown that social media have potential to empower people with disabilities. However, digital accessibility is a new area in China and very few studies have focused on the accessibility of Chinese social media services. This research aims to evaluate the accessibility of Weibo for people with visual impairments. A survey, interviews and user testing were used to identify accessibility issues of Weibo. On the basis of the findings, recommendations are made to improve accessibility.
Universal Design as a Transformative Agent in Education for All Learners
Authors: Craddock Gerald  , McNutt Larry
Published: February 2025

Universal Design (UD) offers a “whole systems approach” and has the capacity to transform the educational environment to encompass all learners. This paper proposes a new framework for a systems change to address the systemic rigidity that often characterises the education sector today. A human development ecological framework combined with Universal Design (UD) and Universal Design for Learning (UDL) with the potential to transform teaching and learning practices and associated policies, procedures and services for the benefit of all learners.
Support Vector Machines with Neural Network
Authors: Yanagimoto Hidekazu
Published: February 2025

Deep learning is paid attention to by many researchers but it is not understandable because of its complex architecture and a black box of data processing. However, deep learning can construct appropriate features from raw data. On the other hand, statistical machine learning is understandable theoretically but needs features capturing characteristics of input data. If deep learning and statistical machine learning are combined, some efforts to construct machine learning decreases. In the paper a goal is to combine deep learning with statistical machine learning, support vector machines and to reduce manual setting efforts. To realize it a neural network constructs a kernel function and linear support vector machines constructs a discriminative hyperplane. In some classification tasks of UCI Machine Learning Repository the proposed method was evaluated. We confirmed the proposed method achieved the same performance as support vector machines without much adjustment.
A Framework for Idea Mining Evaluation
Authors: Alksher Mostafa Ahmed  , Azman Azreen  , Yaakob Razali  , Abdul Kadir Rabiah  , Mohamed Abdulmajid  , Alshari Eissa
Published: February 2025

Idea mining is a new research topic which is gaining momentous attention among knowledge engineering research community. It aims to extend the benefits of the information retrieval by sifting through historical documents so that valuable machine-proposed ideas can be extracted. This paper is mainly focusing on the evaluation of candidate ideas generated by idea mining systems. The main challenge faced by judges is how to evaluate the extracted ideas. Different evaluation methods are critically explored, and evaluation criteria are proposed accordingly. The results showed that the Likert scale measurement is more reliable than binary scale measurement.
Image Segmentation Using Active Contours Driven by Bias Fitted Image Robust to Intensity Inhomogeneity
Authors: Akram Farhan  , Garcia Miguel Angel  , Singh Vivek Kumar  , Saffari Nasibeh  , Sarker Mostafa Kamal  , Puig Domenec
Published: February 2025

In this paper, a novel region-based active contour method is proposed based to both correct and segment the intensity inhomogeneous images. A phase stretch transform (PST) kernel is used to compute new intensity means and bias field, which are employed to define a bias fitted image. In the proposed energy function, a new signed pressure force (SPF) function is formulated with a bias image fitted difference, which helps to segment the intensity inhomogeneous objects. A Gaussian kernel is also used to regularize the level set curve, which also removes the computationally expensive re-initialization. Finally, the proposed method is compared with the state-of-the-art both qualitatively and quantitatively using the synthetic and real brain magnetic resonance (MR) images, which shows it yields the best segmentation and correction results.
FoodPlaces: Learning Deep Features for Food Related Scene Understanding
Authors: Sarker Md. Mostafa Kamal  , Leyva Maria  , Saleh Adel  , Singh Vivek Kumar  , Akram Farhan  , Radeva Petia  , Puig Domenec
Published: February 2025

In human smart nutrition systems, environment based food classification has become popular to help analyzing the food intake based on the nutrition related activity. In this paper, we address the problem of food related environments, which refer to different eating places such as, bars, restaurants, coffee shops, etc. using state-of-the-art convolutional neural networks (CNNs). We collected a new dataset on different food related environments by integrating three publicly available datasets: Places365, ImageNet and SUN397. We have named it “FoodPlaces” and it contains 35 different types of classes. In order to achieve satisfactory results on the food related environment recognition, we fine-tuned several state-of-the-art CNNs, such as VGG16, RsNet50 and InceptionV3 using different transfer learning approaches. The results show that the fully fine-tunned InceptionV3 yields 75.22% classification accuracy among the discussed state-of-the-art CNNs.
Antecedents of CIOs' Innovation Capability in Hospitals: Results of an Empirical Study
Authors: Liebe Jan-David  , Esdar Moritz  , Thye Johannes  , Hübner Ursula
Published: February 2025

CIOs' innovation capability is regarded as a precondition of successful HIT adoption in hospitals. Based on the data of 142 CIOs, this study aimed at identifying antecedents of perceived innovation capability. Eight features describing the status quo of the hospital IT management (e.g. use of IT governance frameworks), four features of the hospital structure (e.g. functional diversification) and four CIO characteristics (e.g. duration of employment) were tested as potential antecedents in an exploratory stepwise regression approach. Perceived innovation capability in its entirety and its three sub-dimensions served as criterion. The results show that CIOs' perceived innovation capability could be explained significantly (R2=0.34) and exclusively by facts that described the degree of formalism and structure of IT management in a hospital, e.g. intensive and formalised strategic communication, the existence of an IT strategy and the use of IT governance frameworks. Breaking down innovation capability into its constituents revealed that “innovative organisational culture” contributed to a large extent (R2=0.26) to the overall result sharing several predictors. In contrast, “intrapreneurial personality” (R2=0.11) and “openness towards users” (R2=0.18) could be predicted less well. These results hint at the relationship between working in a well-structured, formalised and strategy oriented environment and the overall feeling of being capable to promote IT innovation.
Optimizing a Query by Transformation and Expansion
Authors: Glocker Katrin  , Knurr Alexander  , Dieter Julia  , Dominick Friederike  , Forche Melanie  , Koch Christian  , Pascoe Pérez Analie  , Roth Benjamin  , Ückert Frank
Published: February 2025

In the biomedical sector not only the amount of information produced and uploaded into the web is enormous, but also the number of sources where these data can be found. Clinicians and researchers spend huge amounts of time on trying to access this information and to filter the most important answers to a given question. As the formulation of these queries is crucial, automated query expansion is an effective tool to optimize a query and receive the best possible results. In this paper we introduce the concept of a workflow for an optimization of queries in the medical and biological sector by using a series of tools for expansion and transformation of the query. After the definition of attributes by the user, the query string is compared to previous queries in order to add semantic co-occurring terms to the query. Additionally, the query is enlarged by an inclusion of synonyms. The translation into database specific ontologies ensures the optimal query formulation for the chosen database(s). As this process can be performed in various databases at once, the results are ranked and normalized in order to achieve a comparable list of answers for a question.
Deep Learning for Magnetic Resonance Fingerprinting: A New Approach for Predicting Quantitative Parameter Values from Time Series
Authors: Hoppe Elisabeth  , Körzdörfer Gregor  , Würfl Tobias  , Wetzl Jens  , Lugauer Felix  , Pfeuffer Josef  , Maier Andreas
Published: February 2025

The purpose of this work is to evaluate methods from deep learning for application to Magnetic Resonance Fingerprinting (MRF). MRF is a recently proposed measurement technique for generating quantitative parameter maps. In MRF a non-steady state signal is generated by a pseudo-random excitation pattern. A comparison of the measured signal in each voxel with the physical model yields quantitative parameter maps. Currently, the comparison is done by matching a dictionary of simulated signals to the acquired signals. To accelerate the computation of quantitative maps we train a Convolutional Neural Network (CNN) on simulated dictionary data. As a proof of principle we show that the neural network implicitly encodes the dictionary and can replace the matching process.
Smart Information Management in Health Big Data
Authors: Muteba A. Eustache
Published: February 2025

The smart information management system (SIMS) is concerned with the organization of anonymous patient records in a big data and their extraction in order to provide needful real-time intelligence. The purpose of the present study is to highlight the design and the implementation of the smart information management system. We emphasis, in one hand, the organization of a big data in flat file in simulation of nosql database, and in the other hand, the extraction of information based on lookup table and cache mechanism. The SIMS in the health big data aims the identification of new therapies and approaches to delivering care.
Connecting Parents to a Pediatric Emergency Department: Designing a Mobile App Based on Patient Centred Care Principles
Authors: Ehrler Frederic  , Siebert Johan N.  , Rochat Jessica  , Schneider Franck  , Galetto Annick  , Gervaix Alain  , Lovis Christian
Published: February 2025

Introduction: Patient centred care fosters a holistic approach of care switching the focus from a disease perspective to a patient's experience perspective. Patient centred care is of particular importance in the context of paediatric emergency medicine. Indeed, parents entering a paediatric emergency department (PED) are usually under stress caused by their children's illness, the unfamiliar setting of the PED and delays of care. All these factors can deteriorate their experience as well as the relationships between healthcare providers, the patients and their parents.
De-Identification of Medical Narrative Data
Authors: Foufi Vasiliki  , Gaudet-Blavignac Christophe  , Chevrier Raphaël  , Lovis Christian
Published: February 2025

Maintaining data security and privacy in an era of cybersecurity is a challenge. The enormous and rapidly growing amount of health-related data available today raises numerous questions about data collection, storage, analysis, comparability and interoperability but also about data protection. The US Health Portability and Accountability Act (HIPAA) of 1996 provides a legal framework and a guidance for using and disclosing health data. Practically, the approach proposed by HIPAA is the de-identification of medical documents by removing certain Protected Health Information (PHI). In this work, a rule-based method for the de-identification of French free-text medical data using Natural Language Processing (NLP) tools will be presented.
The Meaning of Patient Empowerment in the Digital Age: The Role of Online Patient-Communities
Authors: Lamas Eugenia  , Salinas Rodrigo  , Coquedano Carla  , Simon Marie-Pierre  , Bousquet Cedric  , Ferrer Marcela  , Zorrilla Sergio
Published: February 2025

Traditionally, patient empowerment has been used as a strategy for health promotion. The rise of online communities of patients represents a good example of how patient empowerment occurs, independently of the intervention of existing healthcare providers and insurers, allowing thus a more accurate definition of meaning of this concept. We describe two situations related with the development of health-related social networks: (1) The emergence of a new biomedical research model in which patients lead research, shifting the equilibrium of power from the professionals to research subjects themselves, and (2) The emergence of Lay Crowd-Sourced Expertise in these communities, arising from the daily exchange among patients affected by chronic conditions and their relatives, giving place to a new era of bottom-up data generation, previously unknown in biomedical sciences. We enrich these descriptions by analyzing interviews to key actors of these “on line” communities": Michael Chekroun, founder of “Carenity, France”, and Paul Wicks Vice President at “PatientsLikeMe, USA”.
DataWell: Public Involvement in the Development of a Federated Platform for Shared Patient Records in Greater Manchester, U.K.
Authors: Leeming Gary  , Thew Sarah
Published: February 2025

Sharing personal health data for direct care, health improvement, planning and research is recognised as important to improving the quality and safety of care. However, the complexities of sharing data, including technology, information governance and consent issues, means that many projects have difficulty communicating with the public about why they wish to share data, or what the benefits might be. Great Manchester Academic Health Science Network has established a Public Experience Group to help co-design the requirements for a health information exchange, called DataWell, across over 30 health and care organisations in Greater Manchester. This group has allowed the programme to uniquely respond to questions of how consent and data sharing should work with DataWell for direct care, as well as exploring other uses of the data, including planning and research.
DNA Encoding Training Using 3D Gesture Interaction
Authors: Nicola Stelian  , Handrea Flavia-Laura  , Crişan-Vida Mihaela  , Stoicu-Tivadar Lăcrămioara
Published: February 2025

The work described in this paper summarizes the development process and presents the results of a human genetics training application, studying the 20 amino acids formed by the combination of the 3 nucleotides of DNA targeting mainly medical and bioinformatics students. Currently, the domain applications using recognized human gestures of the Leap Motion sensor are used in molecules controlling and learning from Mendeleev table or in visualizing the animated reactions of specific molecules with water. The novelty in the current application consists in using the Leap Motion sensor creating new gestures for the application control and creating a tag based algorithm corresponding to each amino acid, depending on the position in the 3D virtual space of the 4 nucleotides of DNA and their type. The team proposes a 3D application based on Unity editor and on Leap Motion sensor where the user has the liberty of forming different combinations of the 20 amino acids. The results confirm that this new type of study of medicine/biochemistry using the Leap Motion sensor for handling amino acids is suitable for students. The application is original and interactive and the users can create their own amino acid structures in a 3D-like environment which they could not do otherwise using traditional pen-and-paper.
Predict NBA 2016–2017 Regular Season MVP Winner
Authors: Chen Mason
Published: February 2025

This project is to build a statistical model to predict who will win 2017 NBA Most Valuable Player (MVP) Award in the regular season. Team has collected three raw data from public Sports domain: (1) player statistics, (2) team win%, and (3) historical MVP winners. Before building the proto model, the player statistics have been standardized to the Z scale in each player statistics category in order to remove any mean and standard deviation effect. This Z transformation can eliminate any statistics bias or domination from any particular category. The Z scale will also analyze each player's performance as compared to the other top NBA players in the same season. The “MVP Index” has been derived from combining each player's Z statistics with equal weight as a “Uniform” model. To evaluate the model accuracy, team has derived another “Accuracy Index” of predicting the top five MVP players recognized annually. The first “Uniform” model can predict the top five winners at 47% accuracy. Team has further derived the “Weighted” model by adding the weight factor which was calculated based on the dispersion/separation between the top two MVP winners and the remaining players not in top 5. The weight factor will reflect which player statistics categories are more critically contributed to the MVP Award selection process. The “Weighted” model has further improved the Accuracy Index from 47% to 52%. To further optimize the prediction accuracy, authors have added the “Team Winning” factor. Most historical MVP winners were from the teams with best or better regular season records. Authors have assessed the team winning factor based on the “Power” model from power= 0 (equivalent to the Weighted Model), 1, 2, 3, 4, 5, 6 to power= infinity (MVP from the best Team). The MVP Index will be multiplied by the power of the team winning% in the Power model. Power transformation will improve the model accuracy but which may also create any over-fit concern when power level is getting higher. Based on the Power Model, team can improve the Accuracy Index to 70% at Power=3. There is little benefit but more over-fit risk to further increase the power level beyond 3. Authors also used Data Mining Discriminant analysis to rank players into clusters. The Discriminant model accuracy is 55% not better than Power Model. Team will use the Power=3 model to predict 2017 MVP on the first day of each month starting from Dec.1, 2016 until the season end in April, 2017. The final model prediction will be available around middle April, 2017. The same modeling technique can be applied to predict the MVP winner for Olympic event as well as for the other professional sports such as Football, Basketball, and Soccer.
The Extraction Scheme of Substation Target Equipment in Complex Infrared Background
Authors: Wang Yuanbin  , Yin Yang
Published: February 2025

Aiming at the shortcomings of infrared image recognition in intelligent substation, an improved target extraction scheme is proposed. Firstly, the Retinex theory is used to remove the influence of the lighting factor and improve the image brightness effect, and then the improved histogram equalization method based on grayscale transformation of segments is used to improve the image contrast. The region of the device is extracted by the region segmentation algorithm combined with the connected component extraction and the regional growth. The experimental results show that the scheme overcomes the drawbacks of existing methods and has good segmentation effect compared with the traditional method. It is a practical target extraction method for substation equipment.
Designing Robust Spatial Filter for Motor Imagery Electroencephalography Signal Classification in Brain-Computer Interface Systems
Authors: Miao Minmin  , Wang Aimin  , Zeng Hong
Published: February 2025

Effective feature extraction is very important for motor imagery (MI) Electroencephalography (EEG) signal pattern recognition in brain machine interface (BMI) or brain computer interface (BCI) applications. Common spatial patterns (CSP) method is a frequently used machine learning algorithm for discriminative feature extraction in MI related BMIs. Although CSP is a famous and effective method in BMI applications, the intrinsic variations in the EEG signal properties would affect its performance. To address this issue, instead of using the eigenvalues for spatial filter vectors selection as instructed by the traditional CSP approach, we present a novel criterion which considers not only the differences between different classes but also the dissimilarities in the same class in a data-driven manner for robust spatial filter construction. We compared our method against CSP using a public dataset, namely dataset IVa of BCI competition III. The final results of the experiment indicate that our approach gives higher classification accuracy, by reducing the variations in the same class.
Design of an Intelligent Nursing Clinical Pathway and Nursing Order Support System for Traditional Chinese Medicine
Authors: Ding Bao-Fen  , Chang Polun  , Wang Ping  , Li Hai-Ting  , Kuo Ming-Chuan
Published: February 2025

With an in-depth analysis of nursing work in 14 hospitals over a period of two years, one unique total nursing information system framework was established where the nursing clinical pathways are used as the main frame and the nursing orders as the nodes on the frame. We used the nursing order concept with the principles of nursing process. A closed-loop management model composed of the nursing orders was set up to solve nursing problems. Based on the principles of traditional Chinese medicine, we further designed an intelligent support module to automatically deduct clinical nursing pathways to promote standardized management and improve the quality of nursing care. The system has successfully been implemented in some facilities since 2015.
Improving Patient Safety Through the Design and Development of a Computerized Provider Order Entry for Parenteral Nutrition Linked to a Barcode Medication Administration Record
Authors: Jáuregui Oscar I.  , Bruchanski Lucila  , Rizzato Lede Daniel A.  , Otero Carlos M.  , Luna Daniel R.
Published: February 2025

Among adverse events related to medication errors, the defects in parenteral nutrition administration pose a special threat to patient safety. Two high impact strategies to reduce these errors require implementing a Computerized Provider Order Entry and the use of bedside bar-code verification prior to medication administration. In this study, we share the deep field analysis of the current workflow performed to include inpatient bedside barcoding verification for parenteral nutrition administration in a large academic health center. Then, we propose a process optimization and a new parenteral nutrition ordering tool embedded in the prescription module. Structuring physicians' ordering and the bar-code verification of administration can increase patient safety. The next steps would involve the creation of a Clinical Decision Support System to improve patient nutrient goals.
Procedure for Reconstruction of a Predictive Score of Severe Deterioration in Inpatients
Authors: Navas Hernán  , Bourdin Elián
Published: February 2025

Adequate recording of patients' physiological parameters provides vital information for health teams. Up to 80% of general admission patients have physiological parameters outside the normal range within 24 hours prior to transfer to the intensive care unit. Early warning systems analyze these data with the aim of detecting early deterioration in patients, which support medical decision making for reducing morbimortality. There are more than 100 systems for detecting patients at risk. Particularly NEWS has a greater ability to discriminate patients at risk of cardiac arrest, unplanned admission to ICU, and death. Sanatorio Finochietto has a commercial Health Information System. In order to exploit the available information, an algorithm capable of constituting a score value associated with NEWS has been developed from the combination of measurements made at different times. The reconstruction procedure allowed a greater number of full records. We had a 75% coincidence with real-time comparison.
Framework of Performance Measures for Health Information Exchange (HIE)
Authors: Mihoko Okada  , Haku Ishida  , Sunao Watanabe  , Yoshimune Shiratori
Published: February 2025

Health Information Exchange (HIE) is the most prevelant patient information sharing technology currently in use. Although a number of regional healthcare information systems exist in Japan, little is known about the effectiveness of the systems or how effectiveness should be measured. As an approach to this issue, we developed a framework for measuring effectiveness of HIE using the dimensions for health indicators from ISO/TS 21667:2004 “Health Indicators Conceptual Framework”. Three phases for measuring HIE are defined: Phase I: the static aspects of a system; Phase II: the use of the system; Phase III: the outcomes of the use of the system. Complex factors involved in HIE are organized and objectives of evaluation are made clear. The domains to which measures are applied and categories of measures are defined. Sample measures extracted from publications and co-authors' studies are discussed. This work is the first step towards the systematic development of a framework of measures of the effectiveness of HIE.
Factors Affecting the Time to Occurrence of Hospital-Acquired Pressure Ulcers Using EHR Data
Authors: Park Seul Ki  , Park Hyeoun-Ae
Published: February 2025

This study examined factors affecting the time to occurrence of hospital-acquired pressure ulcers using electronic health records (EHR) data in a critical care setting. The subjects were 202 patients who were admitted to a tertiary hospital between January 2015 and May 2016 and developed pressure ulcers. In total, 61 risk factors for pressure ulcers were extracted from nine different report forms and analyzed using univariate and multiple linear regression analyses. The univariate analysis identified 33 significant factors, and 11 factors remained significant in the multiple regression analysis. Patients with decreased consciousness and those on ventilators tended to develop pressure ulcers during the early stage of hospitalization. Patients taking sedative-hypnotics, anti-inflammatory drugs, steroids, and anticoagulants, those in renal failure, and those who consulted a nutritionist, or had a gastrointestinal or tracheostomy tube or diarrhea tended to develop pressure ulcers at a later stage of hospitalization.
Making Sense of Patient-Generated Health Data for Interpretable Patient-Centered Care: The Transition from “More” to “Better”
Authors: Hsueh Pei-Yun Sabrina  , Dey Sanjoy  , Das Subhro  , Wetter Thomas
Published: February 2025

The rise of health consumers and the accumulation of patient-generated health data (PGHD) have brought the patient to the centerstage of precision health and behavioral science. In this positional paper we outline an interpretability-aware framework of PGHD, an important but often overlooked dimension in health services. The aim is two-fold: First, it helps generate practice-based evidence for population health management; second, it improves individual care with adaptive interventions. However, how do we check if the evidence generated from PGHD is reliable? Are the evidence directly deployable in realworld applications? How to adapt behavioral interventions for each individual patient at the touchpoint given individual patients' needs? These questions commonly require better interpretability of PGHD-derived patient insights. Yet the definitions of interpretability are often underspecified. In the position paper, we outline an interpretability-aware framework to handle model properties and techniques that affect interpretability in the patient-centered care process. Throughout the positional paper, we contend that making sense of PGHD systematically in such an interpretability-aware framework is preferrable, because it improves on the trustworthiness of PGHD-derived insights and the consequent applications such as person-centered comparative effectiveness in patient-centered care.
Strengthening Data Confidentiality and Integrity Protection in the Context of a Multi-Centric Information System Dedicated to Autism Spectrum Disorder
Authors: Ben Said Mohamed  , Robel Laurence  , Golse Bernard  , Jais Jean Philippe
Published: February 2025

Autism spectrum disorders (ASD) are complex neuro-developmental disorders affecting children in early age. Diagnosis relies on multidisciplinary investigations, in psychiatry, neurology, genetics, electrophysiology, neuro-imagery, audiology, and ophthalmology. To support clinicians, researchers, and public health decision makers, we developed an information system dedicated to ASD, called TEDIS. It was designed to manage systematic, exhaustive and continuous multi-centric patient data collection via secured internet connections. TEDIS will be deployed in nine ASD expert assessment centers in Ile-DeFrance district. We present security policy and infrastructure developed in context of TEDIS to protect patient privacy and clinical information. TEDIS security policy was organized around governance, ethical and organisational chart-agreement, patients consents, controlled user access, patients' privacy protection, constrained patients' data access. Security infrastructure was enriched by further technical solutions to reinforce ASD patients' privacy protection. Solutions were tested on local secured intranet environment and showed fluid functionality with consistent, transparent and safe encrypting-decrypting results.
SMS Education for the Promotion of Diabetes Self-Management in Low & Middle Income Countries: A Randomized Controlled Trial in Egypt
Authors: Abaza Haitham  , Marschollek Michael  , Schulze Mareike
Published: February 2025

Aiming to assess the impact of SMS messages on glycemic control and self-management, we conducted a 12-week RCT at MUST hospital in Cairo-Egypt. Outcomes included change in HbA1c, BG levels, treatment and medication adherence, self-efficacy, and diabetes knowledge. 34 intervention and 39 control patients completed the study. HbA1c did not differ significantly (p = 0.406) between groups but secondary outcomes varied considerably. The effectiveness of SMS over paper-based methods still needs further investigation.
Rapid Development and Distribution of Mobile Media-Rich Clinical Practice Guidelines Nationwide in Colombia
Authors: Flórez-Arango José F.  , Sriram Iyengar M.  , Caicedo Indira T.  , Escobar German
Published: February 2025

Development and electronic distribution of Clinical Practice Guidelines production is costly and challenging. This poster presents a rapid method to represent existing guidelines in auditable, computer executable multimedia format. We used a technology that enables a small number of clinicians to, in a short period of time, develop a substantial amount of computer executable guidelines without programming.
The Development of mWellcare, an mHealth System for the Integrated Management of Hypertension and Diabetes in Primary Care
Authors: Jindal Devraj  , Gupta Priti  , Jha Dilip  , Ajay Vamadevan S.  , Jacob Pramod  , Mehrotra Kriti  , Perel Pablo  , Nyong Jonathan  , Roy Ambuj  , Tandon Nikhil  , Prabhakaran Dorairaj  , Patel Vikram
Published: February 2025

This paper describes development of mhealth application “mWellcare” for the integrated management of hypertension and diabetes in public primary health care settings. mWellcare application was developed in four phases: identifying gaps in usual care; identifying components of intervention; developing intervention; evaluating acceptability and feasibility through pilot testing. Final version of mWellcare application is capable of computing personalized evidence-based management plan for hypertension, diabetes and co-morbid conditions (depression and alcohol use disorder).
Empathy Bot: Conversational Service for Psychiatric Counseling with Chat Assistant
Authors: Oh Kyo-Joong  , Lee DongKun  , Ko ByungSoo  , Hyeon Jonghwan  , Choi Ho-Jin
Published: February 2025

There are earlier studies for psychiatric counseling using chat bots. These studies have not considered the user's emotional status and ethical judgment to provide interventions. This paper proposes an intelligent assistant for psychiatric counseling that understands dialogues using high-level features of natural language understanding, and multi-modal emotion recognition. A response generation model using machine leaning provides suitable responses for clinical psychiatric counseling.
A Document-Based EHR System That Controls the Disclosure of Clinical Documents Using an Access Control List File Based on the HL7 CDA Header
Authors: Takeda Toshihiro  , Ueda Kanayo  , Nakagawa Akito  , Manabe Shirou  , Okada Katsuki  , Mihara Naoki  , Matsumura Yasushi
Published: February 2025

Electronic health record (EHR) systems are necessary for the sharing of medical information between care delivery organizations (CDOs). We developed a document-based EHR system in which all of the PDF documents that are stored in our electronic medical record system can be disclosed to selected target CDOs. An access control list (ACL) file was designed based on the HL7 CDA header to manage the information that is disclosed.
Use Contexts and Usage Patterns of Interactive Case Simulation Tools by HIV Healthcare Providers in a Statewide Online Clinical Education Program
Authors: Wang Dongwen
Published: February 2025

We analyzed four interactive case simulation tools (ICSTs) from a statewide online clinical education program. Results have shown that ICSTs are increasingly used by HIV healthcare providers. Smart phone has become the primary usage platform for specific ICSTs. Usage patterns depend on particular ICST modules, usage stages, and use contexts. Future design of ICSTs should consider these usage patterns for more effective dissemination of clinical evidence to healthcare providers.
Comparative Analysis of Geriatric and Adult Drug Clinical Trials on ClinicalTrials.gov
Authors: He Zhe  , Langford Aisha
Published: February 2025

Clinical trials generate gold standard medical evidence, but are often criticized for the lack of population representativeness. We performed a comparative meta-analysis of drug trials that focus on older adults (>= 65 years old) and adults (18–64 years old). The major finding is that a higher percentage of geriatric drug trials were terminated or withdrawn than that of adult drug trials.
Usability Evaluation of NLP-PIER: A Clinical Document Search Engine for Researchers
Authors: Hultman Gretchen  , McEwan Reed  , Pakhomov Serguei  , Lindemann Elizabeth  , Skube Steven  , Melton Genevieve B.
Published: February 2025

NLP-PIER (Natural Language Processing – Patient Information Extraction for Research) is a self-service platform with a search engine for clinical researchers to perform natural language processing (NLP) queries using clinical notes. We conducted user-centered testing of NLP-PIER's usability to inform future design decisions. Quantitative and qualitative data were analyzed. Our findings will be used to improve the usability of NLP-PIER.
The Study of Hot Spots on Hepatitis B Dissertation Based on Co-Word Analysis in China
Authors: Zhang W.  , Wang Y.B.  , Zhang X.Z.  , Duan H.M.
Published: February 2025

Doctoral dissertations and master's theses of “hepatitis B” (HB) in CNKI database were retrieved to explore the hot spots on HB research field in China, we processed, visualized the data above, and analyzed those data by using co-word analysis informetrics method. Then, the figure for co-occurrence analysis of high-frequency keywords in theses on HB were plotted, which represented eight topics, could help health staff to understand hot topics in this field.
Virtual Reality in Nursing: Nasogastric Tube Placement Training Simulator
Authors: Choi Kup-Sze
Published: February 2025

A virtual reality (VR) based training simulator developed for nasogastric tube (NGT) placement is presented. It leverages the advantages of VR technology – safety, flexibility, interactivity and quantitative assessment – to speed up the learning curve of NGT placement. The simulator demonstrates the potential of VR for nurse education.
Development of a Data Collection Tool for MbHIS-QUAL: Evaluation of the Quality of Morbidity Data in Routine Health Information Systems (RHISs) in Hospitals
Authors: Hanmer Lyn  , Nicola Edward  , Bradshaw Debbie
Published: February 2025

The quality of morbidity data in multiple routine inpatient records in a sample of South African hospitals is being assessed in terms of data accuracy and completeness. Extensive modification of available data collection tools was required to make it possible to collect the required data for the study.
Digital Divide and Health Disparities in China: Data from a National Longitudinal Survey of CHARLS
Authors: Hong Y. Alicia  , Zhou Zi  , Fang Ya
Published: February 2025

The China Health and Retirement Longitudinal Study (CHARLS, 2013) data was used to investigate internet use and mobile phone ownership in older Chinese adults and examine digital divide and social economic status and mobile technology adoption and health outcomes associations. Results suggest a significant digital divide associated with not only individual characteristics, but also neighborhood resources. Future eHealth programs should consider the accessibility of mobile tools and develop culturally appropriate programs for different social groups.
DOCtimer: A Timing and Event Recording Tool for Direct Observational Research
Authors: Nolan Matthew E.  , Pickering Brian W.  , Herasevich Vitaly
Published: February 2025

Clinical research often requires direct observation of clinicians performing routine tasks, but few effective data collection instruments exist. We describe the development of DOCtimer – a web-based, platform-independent timing and counting application that allows researchers to easily record numerous tracking elements on a single screen, faciltating robust data collection for direct observational research.
Training of Students for Critical Evaluation of Mobile Health Applications
Authors: Bozikov Jadranka  , Hercigonja Szekeres Mira
Published: February 2025

Medical and nursing students need to be trained in critical evaluation of mobile health applications (m-health apps) in order to see their potential and to understand the need for their validation and certification. Students should develop positive attitudes but also critical views on such apps in order to be prepared for responsible and ethical use of m-health in their future professional practice.
Mapping HL7 CDA R2 Formatted Mass Screening Data to OpenEHR Archetypes
Authors: Kobayashi Shinji  , Kume Naoto  , Yoshihara Hiroyuki
Published: February 2025

Mass screening of adults was performed to manage employee healthcare. The screening service defined the data collection format as HL7 Clinical Document Architecture (CDA) R2. To capture mass screening data for nationwide electronic health records (her), we programmed a model within the CDA format and mapped the data items to the ISO13606/openEHR archetype for semantic interoperabiilty.
Terminology Status APIs – Mapping Obsolete Codes to Current RxNorm, SNOMED CT, and LOINC Concepts
Authors: Peters Lee  , Nguyen Thang  , Bodenreider Olivier
Published: February 2025

We created the Terminology Status Application Programming Interface (API) to assist users in mapping obsolete codes to current RxNorm, SNOMED CT and LOINC concepts. Use cases include support for information retrieval, maintenance of value sets, and analytics of legacy clinical databases. Our terminology status APIs typically receive over 4 million calls per month on average.
Using an Ontology-Based Approach to Handle Author Affiliations in a Large Biomedical Citation Database
Authors: Sun Haixia  , Li Junlian  , Wu Yingjie  , Wang Lei  , Fung Kin Wah
Published: February 2025

To handle differences in affiliation names submitted with biomedical journal articles, we build an affiliation knowledge base named Authority File for Affiliations (AFA) based on ontology principles. There are currently 113,700 affiliation concepts with about 583,700 affiliation names. The AFA becomes an essential tool in managing citation information and data analysis.
Application of Information Technology in the Outpatient Service Optimization
Authors: Zhang Xiaoying
Published: February 2025

In a hierarchical diagnosis and treatment policy local tertiary hospitals assume the majority of clinic service, improving patient medical experience and enhancing service quality. Information technologies such as comprehensive self-services, and palm medical APPs can help solve these problems.
Modeling a System for Generating Structured Reports
Authors: Dutra da Costa Lorena  , Cordeiro d'Ornellas Marcos
Published: February 2025

The purpose of this research is to make the medical report generation process more practical, fast and reliable, both for the health professional and for the patient. We created an ontology and modeling of a structured report (SR) Standard DICOM SR.
Automatic Loading of Problems Using a Comorbidities Subset: One Step to Organize and Maintain the Patient's Problem List
Authors: Márquez Fosser Santiago  , Gaiera Alejandro  , Otero Carlos  , Benitez Sonia  , Luna Daniel  , Quiroz Fernán
Published: February 2025

An accurate and updated problems' list is critical in a problem-oriented Electronic Health Record (EHR). The lack of organization and maintenance of the problems limits its value. Certain problems have a larger effect on the clinical evolution of the patient, these are known as Comorbidities. The aim of this paper is to evaluate the impact of the automatic loading of comorbidities in the organization and maintenance of inpatient problems' list using a comorbidities subset.
A Study of Evaluation and Automation Instruction of Management by Law of Community Health Service in China
Authors: Hu Hongpu  , Zhang Yue  , He Yao  , Yu Fan  , Guo Minjiang
Published: February 2025

The goal is to explore a concrete mode for the health administrative department to manage community health service. On the basis of existing health laws and regulations, the study synthesized computer technology, set up the automation system of community health service supervision and management, drew up management norm, management procedure, evaluation system, designed corresponding software, and then completed the spot usage. Four changes of community health service management are realized.