bluuebunny/crossref_metadata_2025 huggingface dataset:
Assistive Technology for an Inclusive Society for People with Intellectual Disability
Authors: Owuor John  , Larkan Fiona
Published: February 2025

People with intellectual disability (ID), are some of the most stigmatized and marginalized social groups. Ongoing global initiatives such as the United Nations Convention on the Rights of Persons with Disabilities (UNCPD) and Strategic Development Goals (SDGs) aim to accelerate their inclusion into the society. In many high-income countries, deinstitutionalization of care for people with ID forms part of the broader social inclusion agenda for people with ID into the society. Access to appropriate assistive technology (AT) can mediate the ongoing normalization/inclusion efforts for people with ID. AT can enable users with ID to access societal processes such as education, employment, socialization or independent living. Effective use of AT can also enhance the formation and/or maintenance of interpersonal relationships by people with ID, thus promote their social support.
Usability of Optical Mark Reader Sheet as an Answering Tool in Testing
Authors: Booka Masayuki  , Oku Hidehisa  , Scheller Andreas  , Yamaoka Shintaro
Published: February 2025

The research result on usability of Optical Mark Reader Sheet (OMRS) being used as the standard answering tool is reported. The use of OMRS significantly requires more answer time than the answer time without OMRS, and the use of assistive devices for OMRS has the possibility to reduce the answer time.
Observing Remote Prescription of AT
Authors: Cudd Peter  , Zahid Aejaz  , Friday Marcus
Published: February 2025

A lack of widely accepted guidelines/protocols for remote prescription of assistive technology is noted. This paper reports observations from attempts to use web based videoconferencing with embedded tools for the provision of assistive technology to children with complex needs.
Universal Design Across the Curriculum: Training for Students and Teachers
Authors: MacKeogh Trish  , Hubbard James  , O'Callaghan Kieran
Published: February 2025

Providing an inclusive educational setting for children with disabilities is essential if they are to truly benefit from mainstream education. Universal design (UD) provides a framework to develop our classrooms, materials and methods to accommodate diverse learners and students with special educational needs without the need to retrofit or remove the student from the classroom. This paper outlines the theory and the approach of two training courses on Universal Design developed for teachers and students
Confidence Based Consensus in Environments with High Uncertainty and Incomplete Information
Authors: Ureña Raquel  , Chiclana Francisco  , Fujita Hamido  , Herrera-Viedma Enrique
Published: February 2025

With the incorporation of web 2.0 frameworks the complexity of decision making situations has exponentially increased, involving in many cases many experts, and a potentially huge number of different alternatives, leading the experts to present uncertainty with the preferences provided. In this context, is where Intuitionist fuzzy preference relations plays a key roll as they provide the experts with means to allocate the uncertainty inherent in their proposed opinions. However, in many occasions the experts are unable to give a preference due to different reasons, therefore effective mechanism to cope with missing informations are more than necessary. In this contribution, we present a new GDM approach able to estimate the missing information and at the same time provide a mechanism to bring closer the experts opinions in a iterative process in which the experts confidence plays a key role.
Convolutional Neural Networks for Question Classification in Italian Language
Authors: Pota Marco  , Esposito Massimo  , De Pietro Giuseppe
Published: February 2025

Question Classification (QC) is a very important module, to include into the pipeline usually employed to implement the Question Answering paradigm. Recently, good results have been achieved on the QC task by using Convolutional Neural Networks (CNNs). This approach requires setting a CNN architecture and a huge number of hyperparameters to obtain the desirable achievements, and only little research has been addressed on this activity. Moreover, while the greatest part of research strength focused on English language, very few works dealt with other languages. In this work, an approach based on neural networks is used to classify Italian questions taken from a TREC dataset. In particular, different solutions regarding the CNN architecture are tested, and, according to literature advices, the best settings are searched in the proper ranges, in order to maximize the classification power for the particular case of Italian questions dataset.
Applying Data Analytics Approach in Systematic Literature Review: Master Data Management Case Study
Authors: Haneem Faizura  , Kama Nazri  , Ali Rosmah  , Selamat Ali
Published: February 2025

Systematic Literature Review (SLR) is a structured way of conducting a review that can assist the researcher in analyzing the progress of a specific stream of research. Although there are a number of SLR guidelines proposed by existing researchers, there is still too little attention paid to the approach taken and the tools that could be applied throughout the SLR process. Therefore, this paper attempted to fill the gap by presenting the application of Data Analytics approach in the SLR with the utilization of data mining and text mining technique. It proposed a step-by-step procedure using data analytics approach, and recommended tools to be used in the SLR process. To demonstrate the applicability of the approach, the authors selected a Master Data Management research domain as a case study. Based on this particular application, it can be concluded that this approach is a replicable, effective and output-based approach in conducting an SLR. It is hoped that other researchers would be able to replicate this approach in doing SLR for other research domains such as software engineering and information technology fields of study.
Online Handwritten Signatures Verificaton Using Dynamic Threshold Combined with Local and Global Features
Authors: Nabi Rebwar M.  , Azad Rania  , Nabi Rebaz M.  , Mahmood Sardasht M-Raouf
Published: February 2025

At the present time, due its popularity in today's market online handwritten signature verification (OHSV) has become an interested area of research. Considerable results have been achieved in terms of accuracy and computation so far. However, it is evident that there is still a big room for improvement either in accuracy or computation speed. This paper proposes online handwritten signature verification system. In this study, five signatures have been used as references signature, in which it was found to be very promising. Lastly, a local English signature dataset with 20 participants has been created to evaluate the system performance with two different sessions. The overall performance of the system is promising since 2% of Equal Error Rate (EER) is achieved which is considered as a reasonable performance level for most environments.
Recurrent Neural Conditional Random Fields for Target Identification of Tweets
Authors: Jabreel Mohammed  , Hassan Fadi  , Abdulwahab Saddam  , Moreno Antonio
Published: February 2025

Target-dependent sentiment analysis on Twitter is the problem of identifying the sentiment polarity towards a certain target in a given tweet. All the existing studies of this task assume that the target is known. However, in such tasks, extracting the targets from the text is one of the most important subtasks. In this paper, we propose a model based on Bidirectional Gated Recurrent Units and Conditional Random Fields to identify automatically the targets from the tweets. The model has been evaluated on two benchmarks of tweets, obtaining results which show its superiority over several baseline methods.
IT Decision Making in German Hospitals – Do CEOs Open the Black Box?
Authors: Thye Johannes  , Hübner Ursula  , Hüsers Jens  , Babitsch Birgit
Published: February 2025

Health IT and communication systems are indispensable in German hospitals for clinical as well as administrative process support. However, IT is often regarded as a “black box” for hospital CEOs. Thus, the question arises how can CEOs decide if they do not know what is in the box? In order to answer this question, half-structured interviews with 14 German hospital CEOs were conducted. They revealed three principle decision processes: the supported decision, the joint decision and the corporate level decision. In all cases, the hospital CEO and the CIO interacted to reach the final decision, most strongly in the joint decision mode and least strongly in the corporate decision mode. Only the joint decision mode definitely forced the CEO to open the “black box” of IT. In the era of digitalisation, however, CEOs must develop better competencies to decide over complex matters.
Requirements Analysis for a Clinical Decision Support System Aiming at Improving the Artificial Nutrition of Critically Ill Patients
Authors: Schüttler Christina  , Hinderer Marc  , Kraus Stefan  , Lang Anne-Katharina  , Prokosch Hans-Ulrich  , Castellanos Ixchel
Published: February 2025

Background: Nutrition support is an important aspect regarding the care of critically ill patients. Malnutrition affects the recovery process negatively. However, the impact on the clinical outcome is often underestimated in complex clinical settings due to several factors hindering optimization of nutrition.
A Socio-Technical Analysis of Patient Accessible Electronic Health Records
Authors: Hägglund Maria  , Scandurra Isabella
Published: February 2025

In Sweden, and internationally, there is a movement towards increased transparency in healthcare including giving patients online access to their electronic health records (EHR). The purpose of this paper is to analyze the Swedish patient accessible EHR (PAEHR) service using a socio-technical framework, to increase the understanding of factors that influence the design, implementation, adoption and use of the service. Using the Sitting and Singh socio-technical framework as a basis for analyzing the Swedish PAEHR system and its context indicated that there are many stakeholders engaged in these types of services, with different driving forces and incentives that may influence the adoption and usefulness of PAEHR services. The analysis was useful in highlighting important areas that need to be further explored in evaluations of PAEHR services, and can act as a guide when planning evaluations of any PAEHR service.
Research on Retrieval Algorithm Based on Mass Semantics
Authors: Shen Xianhao  , Liu Zhu  , Niu Qinzhou  , Liu Yi
Published: February 2025

In a specified semantic context, the meaning of a vague concept is different from its literal meaning, which cannot meet the specified needs of the user. The focus of this paper is how to mine valuable implicit information by existing literal information in a specified context. In a specified context, the mass function is used to assign the basic label subset, and the label semantics framework is used to compute the appropriate degree of the corresponding logical expressions of a vague concept in the specified context. At the same time, in order to demonstrate the effectiveness of this method, implicit information mining is carried out on the company size, profession and position on the collaborative ability platform of the Chamber of commerce. The combination of three factors, appropriate degree of different individuals is computed in a specified semantic context. The experimental results show that the proposed method can effectively mine the implicit information in the specified context, which is more consistent with the actual situation.
Mapping the Electronic Health Record: A Method to Study Display Fragmentation
Authors: Senathirajah Yalini  , Wang Jinglu  , Borycki Elizabeth  , Kushniruk Andrek
Published: February 2025

Electronic health records have often been criticized for poor interaction design. One major problem is the ‘display fragmentation problem’ i.e. the fact that conventional EHRs require the user to view many screens and retain information in memory or external tools rather than being able to view all relevant information together, increasing cognitive load and the possibility of errors and inefficiency. We describe a method for evaluating and depicting the extent of display fragmentation and discuss its potential uses in comparing systems, identifying navigation pathways and information juxtaposition, and improving EHR interaction design.
E-Health Literacy and Health Information Seeking Behavior Among University Students in Bangladesh
Authors: Islam Md. Mohaimenul  , Touray Musa  , Yang Hsuan-Chia  , Poly Tahmina Nasrin  , Nguyen Phung-Anh  , Li Yu-Chuan (Jack)  , Syed Abdul Shabbir
Published: February 2025

Web 2.0 has become a leading health communication platform and will continue to attract young users; therefore, the objective of this study was to understand the impact of Web 2.0 on health information seeking behavior among university students in Bangladesh. A random sample of adults (n = 199, mean 23.75 years, SD 2.87) participated in a cross-sectional, a survey that included the eHealth literacy scale (eHEALS) assessed use of Web 2.0 for health information. Collected data were analyzed using a descriptive statistical method and t-tests. Finally logistic regression analyses were conducted to determine associations between sociodemographic, social determinants, and use of Web 2.0 for seeking and sharing health information. Almost 74% of older Web 2.0 users (147/199, 73.9%) reported using popular Web 2.0 websites, such as Facebook and Twitter, to find and share health information. Current study support that current Web-based health information seeking and sharing behaviors influence health-related decision making.
Competencies for Effective Use of Online Depression Information Among College Students
Authors: Gu Yulong  , Kalibatseva Zornitsa  , Song Xu
Published: February 2025

Mental health issues such as depression are rising among young people, who may benefit from online depression related information. However, the competencies required to search for and evaluate health information on the Internet were reported as poor among this population. We designed a web-based questionnaire survey including four case scenarios to understand how college students use online depression information, and what competencies or factors may facilitate effective use of the online resources.
Intelligent Digital Environment for Wellbeing and Health
Authors: Hunter Inga  , Lockhart Caroline  , Elers Phoebe  , Whiddett Dick  , Guesgen Hans
Published: February 2025

This three-phase project seeks to identify the user-requirements and develop a novel and unobtrusive technology platform interpreting and integrating diverse sources of information from a variety of digital devices monitoring the health and wellbeing of an older person with social media networking. This technology platform will communicate that information within an individualised support network thus supporting the older person to ‘age in place’. This poster presents the process and preliminary results of phase one.
Factors Influencing Progress of Health Information Exchange Organizations in the United States
Authors: Overhage Lauren M.  , Covich-Bordenick Jennifer  , Li Xiouchun  , Overhage J. Marc
Published: February 2025

Progress is being made toward improved healthcare interoperability in the United States, but exchange between electronic health records alone is insufficient. Using data from the eHealth Initiative's Annual Survey of Health Information Exchange, we developed models of HIE financial and operational progress. Our analysis suggests that organizations that focus on enabling exchange thorugh education and policy need to be considered separately from those focused on the actual exchange. The associations between characteristics and progress in data exchanging HIEs suggest that diversity of participants as both originators and receivers of data and breadth of data are important underlying success factors.
Mining Associations Between Genes and Clinical Conditions of Breast Cancer by Using Gene Expression Data
Authors: Hou Yuefang  , Zhang Hao  , Zhang Han  , Cui Lei
Published: February 2025

Recent studies have identified some genes related to cancer phenotypes, but lack of comprehensive clinical information. Here we present an integrated data mining method to find associations between genes and multiple clinical conditions of breast cancer by using gene expression data from Gene Expression Omnibus. The associated modules of genes and clinical conditions were built and some potential related genes were suggested.
Identifying Patients' Smoking Status from Electronic Dental Records Data
Authors: Patel Jay  , Siddiqui Zasim  , Krishnan Anand  , Thyvalikakath Thankam
Published: February 2025

Smoking is a significant risk factor for initiation and progression of oral diseases. A patient's current smoking status and tobacco dependency can aid clinical decision making and treatment planning. The free-text nature of this data limits accessibility causing obstacles during the time of care and research utility. No studies exist on extracting patient's smoking status automatically from the Electronic Dental Record. This study reports the development and evaluation of an NLP system for this purpose.
Using a Simulation Modelling Approach to Manage Outpatient Department Waiting Time at the National Hospital of Sri Lanka
Authors: Silva S.N.  , Hewapathirana R.H.  , Jayatilleke W.M.A.U.
Published: February 2025

A simulation modeling approach was used to determine the optimal human resource solutions for the main functions of the OPD by observing 384 conveniently selected patients at the National Hospital of Sri Lanka. This work seems to be optimized by increasing the morning shift doctors, causing minimal disturbance and inconvenience to the administration and the workers.
Evaluation of the Anonymity and Utility of De-Identified Clinical Data Based on Japanese Anonymization Criteria
Authors: Kimura Eizen  , Hasegawa Satoshi  , Chida Koji  , Gamo Shoko  , Irino Satoshi  , Ishida Haku  , Kurihara Yukio
Published: February 2025

We analyze the deterioration of clinical data quality due to anonymization. The result shows that data quality remained high with micro-aggregation and also verify the availability of noise addition to prevent illegal re-identification by matching another personal data.
Correcting Ontology Errors Simplifies Visual Complexity
Authors: Liu Hao  , Zheng Ling  , Perl Yehoshua  , Chen Yan  , Elhanan Gai
Published: February 2025

In previous research we have shown that hierarchically complex overlapping concepts have a higher error rate of errors versus control concepts. In this poster we show an exmaple from Neoplasm concepts of the NCI thesaurus (NCIt) demonstrating that erroneous overplapping concepts, reflected in the partial-area units of a partial-area taxonomy, display visual complexity. Furthermore, correcting these erroneous concepts causes visual simplification.
POLE.VAULT: A Semantic Framework for Health Policy Evaluation and Logical Testing
Authors: Shaban-Nejad Arash  , Okhmatovskaia Anya  , Shin Eun Kyong  , Davis Robert L.  , Buckeridge David L.
Published: February 2025

The major goal of our study is to provide an automatic evaluation framework that aligns the results generated through semantic reasoning with the best available evidence regarding effective interventions to support the logical evaluation of public health policies. To this end, we have designed the POLicy EVAlUation & Logical Testing (POLE.VAULT) Framework to assist different stakeholders and decision-makers in making informed decisions about different health-related interventions, programs and ultimately policies, based on the contextual knowledge and the best available evidence at both individual and aggregate levels.
Data Quality of the Chinese National AIDS Information System: A Critical Review
Authors: Chen Hong  , Yu Ping  , Hailey David  , Cui Tingru
Published: February 2025

Thirty-nine electronic English and Chinese articles on data quality assessment of the Chinese AIDS information system were critically reviewed. Some performance assessment related indicators of data quality have improved since the system was launched in 2008. After a thematic analysis of the factors that may affect data quality, four domains were identified. They are data management, data collector, information system, and data collection environment. The findings are useful to guide data quality improvement effort.
A Guide for Constructing Bayesian Network Graphs of Cancer Treatment Decisions
Authors: Cypko Mario A.  , Stoehr Matthaeus  , Oeltze-Jafra Steffen  , Dietz Andreas  , Lemke Heinz U.
Published: February 2025

In complex cancer cases, Bayesian networks can support clinical experts in finding the best patient-specific therapeutic decisions. However, the development of decision networks requires teamwork of at least one domain expert and one knowledge engineer making the process expensive, time-consuming, and prone to misunderstandings. We present a novel method for guided modeling. This method enables domain experts to model collaboratively without the need of knowledge engineers, increasing both the development speed and model quality.
Using Health Information Technology to Enhance Care Outcome Accountability Through Bundled Payments
Authors: Gibbings Rima Artonian  , Wickramasinghe Nilmini
Published: February 2025

Eventhough the US expenditure on health care is almost twice of the Organization for Economic Co-operation and Development (OECD) average, the care quality indicators in the US unfortunately are not reflective of such extra spending (Baird, 2016). To revise this cost and quality imbalance, new models have been recommended (and partially implemented) that will tie health care reimbursement with efficient utcomes. This study offers a technology enabled solution to calcualting approraite bundles.
Promotion of Adequate Exercise for Chronic Disorders' Elderly Through Paced Music
Authors: Kang Gi-Ryong  , Kim Il Kon  , Kim Woo Jin  , Lee Do-Youn
Published: February 2025

South Korean population has been aging at an accelerated rate in recent years and the country will be a hyper-aging nation at 2020. One important issue in an aged society is higher rates of chronic disorders among the population. One of the best means to prevent an increase in severity of chronic disease is making patients exercise regularly. In this paper, we present a mobile app for senior citizens that provides daily exercise recommendations an receive tailored service related to a chronic disorder. In this app, pace (BPM) of played music is regulated to encourage patients to fulfill their daily exercise goal. The combination was constructed by using suggestions of World Health Organization and Korea Sports Promotion Foundation. Through our app, users are guided to exercise daily and regularly with appropriate exercise intensity. Patients can deal with their chronic disorders via our mobile application with increased physical activities.
Can Video Conferencing Facilitate Better Discharge Processes and a Superior Patient Experience?
Authors: Grummet Jeremy  , Wickramasinghe Nilmini  , Haddad Peter  , O'Connor Louise
Published: February 2025

Video conferencing is emerging as a useful clinical tool. Its application has extended to cover home monitoring, psychotherapy, managing patients with chronic diseases, and other various applications. However, utilizing video conferencing capabilities to facilitate discharge processes has to date been sparsely researched. This study explores the possibilities of video conferencing to facilitate better patient discharge processes at a large Australian not-for-profit tertiary healthcare group.
Comparing Inpatient Falls Guidelines to Develop an ICNP
Authors: Jung Miran  , Cho Insook  , Chae Jisun  , Kim Jihye  , Kim Yeunhee
Published: February 2025

This study compared and synthesized clinical guidelines for inpatient falls with the aim of developing an ICNP®-based nursing catalogue for use in electronic nursing records. The identified content will influence nursing services provided to patients and the associated documentation.
Development of a Quick SOFA-Based Sepsis Clinical Decision Support System in a Tertiary Hospital Emergency Department
Authors: Kim Youn-Jung  , Lee Jae-Ho  , Lee Sang-Wook  , Jung Ming-Young  , Kim Won Young
Published: February 2025

New definition of sepsis introduced quick sequential organ failure assessment (qSOFA) score. A qSOFA-based sepsis decision support system was designed and developed in an emergency departement. The system has functions of autmatically retrieving qSOFA score, 3 and 6 hours of sepsis and septic shock treatment bundle, semi-automatic calculation of SOFA score, etc. Early usage and user requests are needed to find aspects of improvement.
Using Fast Healthcare Interoperability Resources (FHIR) for the Integration of Risk Minimization Systems in Hospitals
Authors: Saleh Kutaiba  , Stucke Stephan  , Uciteli Alexandr  , Faulbrück-Röhr Sebastian  , Neumann Juliane  , Tahar Kais  , Ammon Danny  , Schmidt Tobias  , Neumuth Thomas  , Besting Andreas  , Portheine Frank  , Herre Heinrich  , Kaeding André  , Specht Martin
Published: February 2025

With the growing strain of medical staff and complexity of patient care, the risk of medical errors increases. In this work we present the use of Fast Healthcare Interoperability Resources (FHIR) as communication standard for the integration of an ontology- and agent-based system to identify risks across medical processes in a clinical environment.
Accuracy of Decision Support Systems for Breast Cancer – Initial Results
Authors: Simões Priscyla Waleska  , Borges Vicente Ronaldo  , Simões Pires Patrícia Duarte  , de Souza Pires Maria Marlene  , Comunello Eros  , Borges Tomaz Felipe  , Ceretta Luciane Bisognin  , de Carvalho Deborah Ribeiro
Published: February 2025

The aim of this study was to evaluate the accuracy of decision support systems in the diagnosis of breast cancer by means of a systematic review and meta-analysis of studies of diagnostic accuracy. The first step of the research, which consisted of the initial research of abstracts and titles identified from the research strategy in the databases was performed by two researchers independently. In this stage, 622 references were retrieved in the databases and, through a consensus meeting, 183 articles were selected for full reading.
PubMedReco: A Real-Time Recommender System for PubMed Citations
Authors: Samuel Hamman W.  , Zaïane Osmar R.
Published: February 2025

We present a recommender system, PubMedReco, for real-time suggestions of medical articles from PubMed, a database of over 23 million medical citations. PubMedReco can recommend medical article citations while users are conversing in a synchronous communication environment such as a chat room. Normally, users would have to leave their chat interface to open a new web browser window, and formulate an appropriate search query to retrieve relevant results. PubMedReco automatically generates the search query and shows relevant citations within the same integrated user interface. PubMedReco analyzes relevant keywords associated with the conversation and uses them to search for relevant citations using the PubMed E-utilities programming interface. Our contributions include improvements to the user experience for searching PubMed from within health forums and chat rooms, and a machine learning model for identifying relevant keywords. We demonstrate the feasibility of PubMedReco using BMJ's Doc2Doc forum discussions.
In Search of a Digital Health Compass to Navigate the Health System
Authors: Chronaki Catherine  , Stegwee Robert  , Moen Anne
Published: February 2025

Healthcare systems increasingly rely on digital technologies to sustain costs and improve access to quality care. Data drive a wave of automation aspiring to improve productivity by forging connections between health and wellness, medical research, and clinical decision support. Mobile apps and patient-generated data combined with provider recordings pave the way towards personalized care pathways and just-in time access to health services. Navigating the health ecosystem becomes challenging as roles and relationships change. This paper reflects on the digital health compass to navigate the health system using one's own data. Health information technology standards are at the core of the compass, to tap the potential of shared aggregate data and sustain trust. The notion of the patient summary as a window to one's health is used as an example to drive our call for action for health informatics to develop methods to calibrate the digital health compass and feed on ‘my data’, respecting ‘my decision’, to fuel ‘our ePower’.
Measurement of Respiration Rate and Depth Through Difference in Temperature Between Skin Surface and Nostril by Using Thermal Image
Authors: Jeong Hieyong  , Matsuura Yutaka  , Ohno Yuko
Published: February 2025

The purpose of the present study was to propose a method to measure a respiration rate (RR) and depth at once through difference in temperature between the skin surface and nostril by using a thermal image. Although there have been a lot of devices for contact RR monitoring, it was considered that the subjects could be inconvenienced by having the sensing device in contact with their body. Our algorithm enabled us to make a breathing periodic function (BPF) under the non-contact and non-invasive condition through temperature differences near the nostril during the breath. As a result, it was proved that our proposed method was able to classify differences in breathing pattern between normal, deep, and shallow breath (P < 0.001). These results lead us to conclude that the RR and depth is simultaneously measured by the proposed algorithm of BPF without any contact or invasive procedure.
Assessing the Representation of Occupation Information in Free-Text Clinical Documents Across Multiple Sources
Authors: Lindemann Elizabeth A.  , Chen Elizabeth S.  , Rajamani Sripriya  , Manohar Nivedha  , Wang Yan  , Melton Genevieve B.
Published: February 2025

There has been increasing recognition of the key role of social determinants like occupation on health. Given the relatively poor understanding of occupation information in electronic health records (EHRs), we sought to characterize occupation information within free-text clinical document sources. From six distinct clinical sources, 868 total occupation-related sentences were identified for the study corpus. Building off approaches from previous studies, refined annotation guidelines were created using the National Institute for Occupational Safety and Health Occupational Data for Health data model with elements added to increase granularity. Our corpus generated 2,005 total annotations representing 39 of 41 entity types from the enhanced data model. Highest frequency entities were: Occupation Description (17.7%); Employment Status – Not Specified (12.5%); Employer Name (11.0%); Subject (9.8%); Industry Description (6.2%). Our findings support the value of standardizing entry of EHR occupation information to improve data quality for improved patient care and secondary uses of this information.
A Mobile System for Music Anamnesis and Receptive Music Therapy in the Personal Home
Authors: Denecke Kerstin
Published: February 2025

Receptive music therapy is active hearing of music that is specifically selected to cause a certain effect on a person, such as pain reduction, mental opening, confrontation etc. This active, guided hearing could be helpful as a supporting ritual for patients at home and could extend traditional therapy. However, patients are often unable to select the music pieces that might be helpful for them in a current situation. We are suggesting a self-learning decision support system that allows a patient to answer questions on music anamnesis, is ready for inclusion into an electronic health record, and which enables a therapist to compile a therapeutic music program for the patient at home. Beyond this, the system also suggests appropriate music and duration of listening based on the patient's reported current mental state. In this paper, a concept for such a mobile system for receptive music therapy will be proposed.
Envisioning Precision Healthcare Informatics: A Unified Framework
Authors: Ramaprasad Arkalgud  , Sastry Nanda Kumar Bidare  , Syn Thant
Published: February 2025

We present a unified framework for envisioning precision healthcare informatics (PHI). The framework, presented as a high-level ontology, deconstructs PHI into six dimensions derived from the informatics and healthcare disciplines—the structure, function, and semiotics of informatics, and the stakeholders, care, and value of precision healthcare. Each dimension is articulated as a taxonomy of its constituent elements. Thus, the framework encapsulates the combinatorial complexity of PHI and can be used to describe its 37,800 potential components in natural English. The framework will help envision PHI systematically, systemically, an symmetrically in contrast to the often simplified, selective, and skewed approaches. The framework can be used to map the state-of-the-research, -practice, and -policy on PHI, discover the gaps within and between the states, and develop a roadmap for the future. It can be scaled and extended as PHI evolves by adding dimensions, and extending/refining the taxonomies.
Identifying Biomarkers of Hepatocellular Carcinoma Based on Gene Co-Expression Network from High-Throughput Data
Authors: Zhang Ying  , Liu Zhiping  , Li Jing-song
Published: February 2025

In this paper, we proposed an approach systematically based on the use of gene co-expression network analyses to identify potential biomarkers for Hepatocellular Carcinoma (HCC). With the analysis of differential gene expression, we first selected candidate genes closely related to HCC from the whole genome on a large scale. By identifying the relationships between each two genes, we built up the gene co-expression network using Cytoscape software. Then the global network was clustered into several sub-modules by Markov Cluster Algorithm (MCL). And, GO-Analysis was carried out for these identified gene modules to further explore the genes obviously associated with the dysfunctions of HCC, and in result we find Hexokinase 2 (HK2) and Krüppel-like Factor 4 (KLF4) as potential candidate biomarkers to provide insights into the mechanism of the development of HCC. Finally, we evaluated the disease classification results via an SVM-based machine learning method to verify the accuracy of the classification
An Interactive Platform to Visualize Data-Driven Clinical Pathways for the Management of Multiple Chronic Conditions
Authors: Zhang Yiye  , Padman Rema
Published: February 2025

Patients with multiple chronic conditions (MCC) pose an increasingly complex health management challenge worldwide, particularly due to the significant gap in our understanding of how to provide coordinated care. Drawing on our prior research on learning data-driven clinical pathways from actual practice data, this paper describes a prototype, interactive platform for visualizing the pathways of MCC to support shared decision making. Created using Python web framework, JavaScript library and our clinical pathway learning algorithm, the visualization platform allows clinicians and patients to learn the dominant patterns of co-progression of multiple clinical events from their own data, and interactively explore and interpret the pathways. We demonstrate functionalities of the platform using a cluster of 36 patients, identified from a dataset of 1,084 patients, who are diagnosed with at least chronic kidney disease, hypertension, and diabetes. Future evaluation studies will explore the use of this platform to better understand and manage MCC.
What Do They Mean by “Health Informatics”? Health Informations Posts Compared to Program Standards
Authors: Jones Josette F.  , Zhang Enming  , Kulanthaivel Anand  , Katta Shilpa
Published: February 2025

There is a lack of alignment between and within the competencies and skills required by health informatics (HI) related jobs and those present in academic curriculum frameworks. This study uses computational topic modeling for gap analysis of career needs vs. curriculum objectives. The seven AMIA-CAHIIM-accepted core knowledge domains were used to categorize a corpus of HI-related job postings (N = 475) from a major United States-based job posting website. Computational modeling-generated topics were created and then compared and matched to the seven core knowledge domains. The HI-defining core domain, representing the intersection of health, technology and social/behavioral sciences matched only 45.9% of job posting content. Therefore, the authors suggest that bidirectional communication between academia and industry is needed in order to better align educational objectives to the demands of the job market.
Serious Games for Parkinson's Disease Fine Motor Skills Rehabilitation Using Natural Interfaces
Authors: Foletto Antônio Augusto  , Cordeiro d'Ornellas Marcos  , Cervi Prado Ana Lucia
Published: February 2025

Parkinson's Disease rehabilitation can be long and boring being difficult to maintain patient engagement on therapy programs. Novel technologies are allowing computer games to be played throught natural interfaces. This paper presents the development and assessment of a system of serious games for fine motor skills rehabilitation using natural interfaces. The games were assessed throught a questionnaire that evaluated the game experience through seven components: immersion, flow, competence, tension, challenge and positive and negative affect. In addition, a conceptual framework for development of serious games for fine motor skills rehabilitation was proposed. The results from the quantitative questionnaire suggested that the player experience was positive on all components assessed. Also, player experience between the three games was statistically the same, implying that the games can be used with consistency in a physical therapy rehabilitation program.
50th Anniversary International Medical Informatics Association (IMIA) History Working Group and Its Projects
Authors: Kulikowski Casimir A.  , Mihalas George  , Greenes Robert  , Yacubsohn Valerio  , Park Hyeoun-Ae
Published: February 2025

The IMIA History Working Group has as its first goal the editing of a volume of contributions from pioneers and leaders in the field of biomedical and health informatics (BMHI) to commemorate the 50th anniversary of IMIA's predecessor IFIP-TC4. This paper describes how the IMIA History WG evolved from an earlier Taskforce, and has focused on producing the edited book of original contributions. We describe its proposed outline of objectives for the personal stories, and national and regional society narratives, together with some comments on the evolution of Medinfo meeting contributions over the years, to provide a reference source for the early motivations of the scientific, clinical, educational, and professional changes that have influenced the historical course of our field.
Design a Learning-Oriented Fall Event Reporting System Based on Kirkpatrick Model
Authors: Zhou Sicheng  , Kang Hong  , Gong Yang
Published: February 2025

Patient fall has been a severe problem in healthcare facilities around the world due to its prevalence and cost. Routine fall prevention training programs are not as effective as expected. Using event reporting systems is the trend for reducing patient safety events such as falls, although some limitations of the systems exist at current stage. We summarized these limitations through literature review, and developed an improved web-based fall event reporting system. The Kirkpatrick model, widely used in the business area for training program evaluation, has been integrated during the design of our system. Different from traditional event reporting systems that only collect and store the reports, our system automatically annotates and analyzes the reported events, and provides users with timely knowledge support specific to the reported event. The paper illustrates the design of our system and how its features are intended to reduce patient falls by learning from previous errors.
Interoperability of Medication Classification Systems: Lessons Learned Mapping Established Pharmacologic Classes (EPCs) to SNOMED CT
Authors: Nelson Scott D.  , Parker Jaqui  , Lario Robert  , Winnenburg Rainer  , Erlbaum Mark S.  , Lincoln Michael J.  , Bodenreider Olivier
Published: February 2025

Interoperability among medication classification systems is known to be limited. We investigated the mapping of the Established Pharmacologic Classes (EPCs) to SNOMED CT. We compared lexical and instance-based methods to an expert-reviewed reference standard to evaluate contributions of these methods. Of the 543 EPCs, 284 had an equivalent SNOMED CT class, 205 were more specific, and 54 could not be mapped. Precision, recall, and F1 score were 0.416, 0.620, and 0.498 for lexical mapping and 0.616, 0.504, and 0.554 for instance-based mapping. Each automatic method has strengths, weaknesses, and unique contributions in mapping between medication classification systems. In our experience, it was beneficial to consider the mapping provided by both automated methods for identifying potential matches, gaps, inconsistencies, and opportunities for quality improvement between classifications. However, manual review by subject matter experts is still needed to select the most relevant mappings.
Characterizing Surgical Site Infection Signals in Clinical Notes
Authors: Skube Steven J.  , Hu Zhen  , Arsoniadis Elliot G.  , Simon Gyorgy J.  , Wick Elizabeth C.  , Ko Clifford Y.  , Melton Genevieve B.
Published: February 2025

Surgical site infections (SSIs) are the most common and costly of hospital acquired infections. An important step in reducing SSIs is accurate SSI detection, which enables measurement quality improvement, but currently remains expensive through manual chart review. Building off of previous work for automated and semi-automated SSI detection using expert-derived “strong features” from clinical notes, we hypothesized that additional SSI phrases may be contained in clinical notes. We systematically characterized phrases and expressions associated with SSIs. While 83% of expert-derived original terms overlapped with new terms and modifiers, an additional 362 modifiers associated with both positive and negative SSI signals were identified and 62 new base observations and actions were identified. Clinical note queries with the most common base terms revealed another 49 modifiers. Clinical notes contain a wide variety of expressions describing infections occurring among surgical specialties which may provide value in improving the performance of SSI detection algorithms.
Spatial Dynamics of The Global Water Quality Analysis System with Semantic-Ordering Functions
Authors: Veesommai Chalisa  , Kiyoki Yasushi
Published: February 2025

The rapid temporal and spatial changes of human population and technology development have resulted in the expansion of agriculture, industrial activity, and deforestation. Those massive expansions affect water resources, especially river. Since the river is the main resource of water in human life, it is crucial to analyze the river water-quality in order to detect the water contamination. In this paper, we present an automatic system for water-quality analysis using several databases and different contexts in dynamic sub-space selection contexts. This system obtains information resources by transforming the sensor-value information to language information. This system aims to monitor, analyze and evaluate the Global Water-quality by using Semantic-ordering functions both in single and multiple parameters. Semantic-ordering is used for spatial-dynamics environmental changes in multiple contexts (aquatic life, agricultural, drinking, fish, industrial usage, and irrigation context). As for the experimental study, four places have been selected as study areas; (1) Hawaii (USA), (2) Pori, (Finland), (3) Riga (Latvia), and (4) Vientiane (Laos). The data resource was acquired from March to September 2016. The result shows that this system is able to analyze and identify the ordering of the different water-quality on different places in the global point of view level and to present the global-scale ranking of water quality.
Visual Data Mining in Software Repositories: A Survey
Authors: Eteläaho Anna  , Soini Jari  , Jaakkola Hannu  , Mattila Anna-Liisa
Published: February 2025

Enormous quantities of data, collected and stored in large numerous data repositories, go unused or underused today, simply because people are unable to visualize the quantities and relationships involved. This huge amount of data has far exceeded our human ability for comprehension without powerful tools. Information visualization and visual data mining can help to deal with the flood of information. We can take advantage of visualization techniques to discover data relationships that are otherwise not easily observable by looking at the “raw data”. Visualization can add significant value when trying to understand not only the raw data available in large software archives, but also the results of data mining. These data are valuable especially in software maintenance activities, understanding software evolution and the socio-technical aspects of software development. Data mining and visualization are focal enablers for information recognition and knowledge discovery from any amount of data repositories. This paper present the results of a survey, which reviews some of the most common visual data mining (VDM) techniques and their usage in the software engineering field. The results indicate what kinds of aspects of the software engineering process are studied using VDM methods, and also the most common VDM methods used in the software engineering context.
Automatic Detection of Significant Updates in Regulatory Documents
Authors: Asooja Kartik  , Foghlú Oscar Ó  , Domhnaill Breiffni Ó  , Marchin George  , McGrath Sean
Published: February 2025

Regulations and legislations are regularly updated, which significantly burdens up the lawyers and compliance officers with a firehose of changes. However, not all changes are significant, and only a percentage of them are of legal importance. This percentage can certainly vary in different types of regulations. This paper focuses on automatic detection or ranking of meaningful legal changes, and presents a preliminary approach based on machine learning for the same, in the domain of Internal Revenue Code (IRC) related regulatory documents. Such system would provide the users with a means to quickly identify significant legal changes.
Cloudy with a Chance of Concepts
Authors: Bardelmeijer Suzanne  , Boer Alexander  , Winkels Radboud
Published: February 2025

In this paper we present the results of a study to see whether automatically generated concept maps help users of legal information systems in understanding the topics of documents they retrieve. A small formative evaluation with novice users is presented. We did not find a significant difference between the ability to connect the correct visualisation to a document between a topic cloud and concept map approach. Topic clouds are probably a little easier to understand quickly in a superficial way.
Timed Contract Compliance Under Event Timing Uncertainty
Authors: Cambronero María-Emilia  , Llana Luis  , Pace Gordon J.
Published: February 2025

Despite that many real-life contracts include time constraints, for instance explicitly specifying deadlines by when to perform actions, or for how long certain behaviour is prohibited, the literature formalising such notions is surprisingly sparse. Furthermore, one of the major challenges is that compliance is typically computed with respect to timed event traces with event timestamps assumed to be perfect. In this paper we present an approach for evaluating compliance under the effect of imperfect timing information, giving a semantics to analyse contract violation likelihood.