bluuebunny/crossref_metadata_2025 huggingface dataset:
Power Spectral Density Estimation from Coprime Samples
Authors: Zhao Yijiu  , Chen Yu  , Yuan Xibin  , Zhang Shanshan
Published: February 2025

Cognitive radio needs high sampling rate to monitor wide frequency band. In this work, we introduce a coprime sampling approach to address this problem. The proposed model consists of two analog-to-digital converters (ADCs), which are clocked at sub-Nyquist coprime rates. In the proposed sampling model, the two ADCs are not required to be synchronously clocked. The two channels simultaneously sample a common signal. The obtained samples are grouped into multiple uniform low speed sequences. We construct the relation between the known autocorrelation functions and unknown average PSD. It is proved that PSD estimation needs to solve an over-determined problem, and the least square algorithm could be used. Simulation results are reported to evaluate the proposed PSD algorithm, and it indicates that the proposed algorithm is feasible.
Multi-Attribute Group Decision Making Based on Bipolar-Valued Fuzzy Multigranulation Rough Sets over Two Universes
Authors: Zhang Chao  , Li Deyu
Published: February 2025

As a significant multi-granularity computing model in the rough set community, multigranulation rough sets (MGRSs) establish multi-dimension and multi-view problem solving methods through providing synthesis and analysis strategies for solution space in different granularity levels, which act as a powerful tool for coping with various complicated multi-attribute group decision making (MAGDM) problems. The main point of interest in this work is to apply the concept of bipolar-valued fuzzy sets (BVFSs) to MGRSs. Firstly, the definition of bipolar-valued fuzzy multigranulation rough sets (BVF MGRSs) over two universes is presented. Then, we construct a MAGDM method on the basis of BVF MGRSs over two universes. Finally, a case study is provided to show the validation and practicality of the newly constructed method.
On Leveraging Facial Emotion Recognition Techniques in Personalized Recommendations
Authors: Khellat-Kihel Souad  , Pandolfo Laura  , Pulina Luca  , Grosso Enrico
Published: February 2025

In the last years, a new set of recommender systems has been recently developed to demonstrate the potential of emotion-based recommendations. Most of them are based on the acquisition and the analysis of data from micro blogging sites in order to predict the users' current emotional state. Considering that emotional aspects play a key role in culture heritage consumption, in this paper we present a facial emotion recognition approach in the context of cultural personalized recommendations. This work represents a first step for obtaining a cultural recommendation system capable to modulate users' emotions to make predictions.
Exploring Different Normalization and Classification Approaches for Mammography Analysis with CNNs
Authors: Perre Ana C.  , Alexandre Luís A.  , Freire Luís C.
Published: February 2025

In order to improve the performance of Convolutional Neural Networks (CNN) in the classification of mammographic images, many researchers choose to apply a normalization method during the pre-processing stage. In this work, we aimed to assess the impact of 6 different normalization methods in the classification performance of 2 CNNs. We have also explored 5 classifiers, being the first one the CNN itself. The other 4 correspond to Support Vector Machine (SVM), Random Forest (RF), Simple Logistic (SL) and Voted Perceptron (VP) classifiers, all of them fed with features extracted from one of the layers – comprised between the sixteenth and the nineteenth – of the CNN. The last 3 classifiers were tested with different options for data testing presentation, according to the Weka software: Supplied Test Set (STS), 10-fold Cross Validation (10-FCV) and Percentage Split (PS). Results indicate that the effect of image normalization in the performance of the CNNs depends on which network is chosen to make the classification; besides, the normalization method that seems to have the most positive impact is the one that subtracts to each image the corresponding image mean and divide it by the standard deviation (best AUC mean values were 0.786 for CNN-F and 0.790 for Caffe; the best run AUC values were, respectively, 0.793 and 0.791. Layer 1 freezing decreased the running time and did not harm the classification performance. Regarding the different classifiers, CNNs used alone with softmax yielded the best results, with the exception of the RF and SL classifiers, both using the 10-FCV and PS options; however, with these options, we cannot guarantee that the test set images are presented for the first time to the network.
Computational Model Exploration of Stimulation Based Paradigm for Detection of Epileptic Systems
Authors: Petkov George  , Kalitzin Stiliyan  , Demuru M.  , Widman G.  , Suffczynski P.  , Lopes da Silva Fernando
Published: February 2025

A stimulation-based measurement paradigm is proposed that can provide a biomarker, which we call “separatrix proximity marker”, able to assess how close is a neural system from an epileptic transition. We use a distributed network of potentially multi-stable local systems that can have different levels of susceptibility for transitions to oscillatory states, considered surrogates of epileptic seizures. The simplest computational model of the bistable system is the complex-valued polynomial model, also called z6model that has been developed by our group. A two-dimensional grid of (9 x 9) z6 units connected with non-linear aperture based interactions is generated for 1000 random sets of parameters, including local parameters and connectivity weights resulting in various degrees of epileptic condition. We investigated an “active” closed-loop protocol where stimulation sequences of increasing amplitudes were delivered to the model system. We found that the separatrix proximity can be used to estimate the relative closeness of the system to the state transition. In this way, our model prescribes a universal biomarker based on the single assumption that the epileptic state is caused by bistable dynamics and does not rely on the specific level of model detail. We also show that the only spatial information needed to do the analysis is the location of the stimulated area and therefore no locally acquired signals are necessary. The findings in this work can be exploited to increase the efficiency and accuracy of pre-surgical epileptogenic zone localisation in cases of focal epileptic seizure onsets or to determine the effective dose and discriminate responsiveness to anti-epileptic drugs.
Working with and Alongside Robots: Forms and Modes of Co-Working
Authors: Seibt Johanna  , Borggreen Gunhild  , Fischer Kerstin  , Hasse Cathrine  , Liu Hin-Yan  , Nørskov Marco
Published: February 2025

The workshop was the fifth event in the series of meetings organized by the Research Network for Transdisciplinary Studies in Social Robotics (TRANSOR, www.transor.org). In line with previous TRANSOR events it served the general aim of including the Humanities into a full-scale interdisciplinary or even transdisciplinary research on Human-Robot Interaction and Social Robotics. The specific aim of this workshop was to contribute to a better understanding of the possible socio-cultural, psychological, and ethical-existential implications of the increased use of social robots in the workplace. The contributions investigated human work experience in different forms and modes of human-robot co-working. Two papers presented classificatory frameworks for distinguishing forms of working with robots (human-robot collaboration) and forms of working alongside artificial social agents. Other papers presented empirical work on new classificatory frameworks.
Robot Clones—New Perspectives in Robophilosophy and Technoimmortality
Authors: Schussler Aura-Elena
Published: February 2025

The problem of total mind uploading (and consciousness) is far from fully solved at present within both the scientific and philosophical paradigms. At the same time, the hypothesis that a robot clone would represent a substitute of one's own person (based on the mindclone argument) questions not only the future ontological status of robot clones (in society) but also its possible personhood quality, in a process whose result is the overthrow of anthropocentrism, seen as the fundamental ideological definition of human nature. Thus, this research is aimed at analyzing technoimmortality in the robot clones paradigm, starting from the theories of Martine Rothblatt and Ray Kurzweil regarding mind uploading in cyberconsciousness and robot clones theory. The overall objective of this paper is to analyze the hypothesis of robot clones' personhood quality, along with the ontological status issue, based on the arguments of Immanuel Kant, Lynne Rudder Baker, and John Searl. The theoretical objective follows to deconstruct the way in which mind cloning (consciousness theory) into a humanoid robot clone, supported by the arguments of Martine Rothblatt, Ray Kurzweil, and Daniel Dennett, actually leads to a simulacrum of our own person—namely a philosophical zombie—according to the theories put forth by Ned Block, David Chalmers, and Searl. The methodology used is that of Rothblatt, Dennett, and Kurzweil's functional argumentation, alongside Block, Searl, and Chalmers's critique of the artificial consciousness of robot clones, completed by Kantian's argumentative critique of robot clone personhood.
Five Principles of Integrative Social Robotics
Authors: Seibt Johanna  , Flensborg Damholdt Malene  , Vestergaard Christina
Published: February 2025

“Integrative Social Robotics” (ISR) is a new approach or general method for generating social robotics applications that are culturally sustainable (Seibt 2016). The paper briefly recapitulates the primary motivation for ISR. Currently social robotics is caught in a compounded version of the Collingridge dilemma—a triple gridlock of description, evaluation, and regulation tasks. In a second step we describe how ISR can overcome this gridlock, presenting five principles that should guide the research, design, and development (RDD) process for applications in social robotics. Characteristic of ISR is to intertwine a mixed method approach (i.e., conducting experimental, quantitative, qualitative, and phenomenological research for the same envisaged application) with conceptual and axiological analysis in philosophy; moreover, ISR is value-driven and abides by the “non-replacement principle”: social robots may only do what humans should but cannot do. In conclusion we suggest, with reference to a classification of different formats of pluridisciplinary research by Nersessian and Newstetter (2013), that ISR may establish social robotics as a new transdiscipline.
An Applied Ethics to Liaise Humanoids with Humans
Authors: Schürer Oliver
Published: February 2025

This text discusses a transdisciplinary experimental development in progress. Its aim is to allow for a liaising, applied ethics in care situations. This is done by facilitating the conditions for ethical behavior of humanoid robots in human care. WeH.A.U.S. is a transdisciplinary research group http://h-a-u-s.org.
We Are Living in a Social Submarine! Children Are Still the Better Adults
Authors: Funk Michael  , Dieber Bernhard
Published: February 2025

In three sections some interactions at the workshop “YuMi in Action! Ethics and Engineering as Transdisciplinary Robotics Performance” and related later reflections are summarized. The primary emphasis is to illustrate what transdisciplinarity is and how transdisciplinarity could work as a certain form of scientific cooperation. Therefore four principles of biomedical ethics are applied to human robot interactions just like the VDI codex of engineering ethics. Methodological fundamentals of transdisciplinary cooperation are discussed related to concrete medical applications of the robot “YuMi.” In the last section the question of transdisciplinary research is (experimentally) related to the metaphor of “social submarines” and concrete practical issues that endanger real transdisciplinarity. Here we close with the question whether children´s more or less unbiased imagination could be seen as a requirement of real transdisciplinarity.
An Information Retrieval Approach for Text Mining of Medical Records Based on Graph Descriptor
Authors: Dudko Alexander  , Endrjukaite Tatiana  , Kiyoki Yasushi
Published: February 2025

This paper describes a new method of data retrieval from free text documents in medical domain. Proposed approach creates the document summary and highlights most important keywords in the text. To achieve this result we process the document natural language text and build a descriptor as an internal representation of the document. This descriptor is a graph with concepts, relations between them, and concept points as a metric of relevance. By means of points in the descriptor the approach performs ambiguity resolution, selects most relevant concepts to display in the summary, and votes for keywords highlighting in the text. Besides the direct representation of identified information in the summary, this work proposes a way to provide extended summary by using additional knowledge about relations between medications, procedures, diseases and anatomy. The described approach helps to speed up analysis and decision making processes by means of providing aggregated summary for a document and highlighting most meaningful parts of the document's text. Experiment results demonstrate that automatic summary generation and keywords highlighting can be successfully performed by the proposed approach to achieve meaningful and highly relevant results.
Cultures in Information Systems Development
Authors: Jaakkola Hannu  , Thalheim Bernhard
Published: February 2025

Modelling is an essential part of information systems development. Models are used for communication between interest groups and inside development teams. Models are also used for transferring baseline artefacts between development phases. Models are mainly developed by humans, which represent certain cultures - national, enterprise, professional, team, project etc. Because of that we claim that models, as well as many other information systems related artefacts are culture dependent. The models are born in certain context and these must be also interpreted by taking the original context into account. In our earlier studies we have analysed the effect of culture in information systems development: culture related aspects in general level, in information search and interaction and in web information systems. We focus now on modelling. Because of that we shortly answer to the question “How cultures differ from each other”. This reviews and synthesis generally accepted frameworks for cultural analysis. In addition we shortly open the results of our earlier studies. Because modelling is a human activity, as well as information systems are used by humans, we integrate the use context into information systems development. The findings of culture analysis are transferred to modelling practices via our framework that defines model as an instrument transferring elements of its development context to the models – we discuss the roles of normal models, deep models and modelling matrix. Finally we will concentrate on the problems of cross-cultural modelling using selected national cultures as an example.
Towards the Assessment of Gold-Standard Alignments Between Legal Thesauri
Authors: Stellato Armando  , Turbati Andrea  , Fiorelli Manuel  , Lorenzetti Tiziano  , Schmitz Peter  , Francesconi Enrico  , Hajlaoui Najeh  , Batouche Brahim
Published: February 2025

In this paper we report on the experience gathered in producing two gold-standard alignment datasets between the European Union thesaurus EuroVoc and two other notable resources adopted in legal environments: the thesaurus of the Italian Senate TESEO and the IATE European terminological resource. The realization of these two resources has been performed in the context of the PMKI project, an European Commission action aiming at creating a Public Multilingual Knowledge management Infrastructure to support e-commerce solutions in a multilingual environment. As of the numerous lexical and terminological resources involved in this project, ontology and thesaurus alignment and, as a consequence, the evaluation of automatically generated alignments, play a pivotal role for the success of the project.
Dealing with Qualitative and Quantitative Features in Legal Domains
Authors: Budán Maximiliano C.D.  , Cobo María Laura  , Martínez Diego I.  , Rotolo Antonino
Published: February 2025

In this work we enrich a formalism for argumentation by including a formal characterization of features related to the knowledge, in order to capture proper reasoning in legal domains. We add meta-data information to the arguments in the form of labels representing quantitative and qualitative data about them. These labels are propagated through an argumentative graph according to the relations of support, conflict, and aggregation between arguments.
Automated Processing of Privacy Policies Under the EU General Data Protection Regulation
Authors: Contissa Giuseppe  , Docter Koen  , Lagioia Francesca  , Lippi Marco  , Micklitz Hans-Wolfgang  , Palka Przemyslaw  , Sartor Giovanni  , Torroni Paolo
Published: February 2025

Two years after its entry into force, the EU General Data Protection Regulation became applicable on the 25th May 2018. Despite the long time for preparation, privacy policies of online platforms and services still often fail to comply with information duties and the standard of lawfulness of data processing. In this paper we present a new methodology for processing privacy policies under GDPR's provisions, and a novel annotated corpus, to be used by machine learning systems to automatically check the compliance and adequacy of privacy policies. Preliminary results confirm the potential of the methodology.
Bat Algorithm Optimized Controller for Automatic Generation Control of Interconnected Thermal Power System
Authors: Kaliannan Jagatheesan  , Baskaran Anand  , Dey Nilanjan  , Ashour Amira S.  , Kumar Rajesh
Published: February 2025

The power balance is considered as most remarkable issue in power generation system. In this proposed work thermal power systems are connected through tie-line. Thermal power system is designed by considering reheat turbine with single stage, governor, and speed regulator unit. Proportional-Integral-Derivative (PID) controller is implemented to regulate the system operation. In this proposed work, the automatic generation control of three-area interconnected reheat thermal power generating system designed and discussed. The PID controller gain values are tuned with the help of more powerful evolutionary Bat Algorithm (BA) procedure. The proposed Bat algorithm tuned controller response was examined by comparing its performance with other optimization technique, namely Genetic Algorithm (GA) and Particle Swam Optimization (PSO) technique tuned controller response. Additionally, different cost functions-based bat algorithm optimized controller responses are presented and compared. The time domain specification parameters are considered for verifying the better-cost function for designing of controller. The simulated responses evident that proposed bat algorithm tuned controller output yield superior performance over GA & PSO tuned controller. Integral Time Square Error (ITSE) cost function-based BA tuned controller give better controlled response during sudden load demand condition in interconnected power system.
Direct Yaw Moment Control for Four-in-Wheel-Motor-Driven Electric Vehicle
Authors: Zhang Yi-xi  , Liu Xiao-dong  , He Yi-lin  , Zhang Kai
Published: February 2025

In order to improve the steering stability of four-in-wheel-motor-driven electric vehicle under complex working condition, this paper proposed a stability control strategy with hierarchical structure for direct yaw moment control of four-in-wheel-motor-driven electric vehicle. Based on the vehicle reference model and actual vehicle state parameters, the fuzzy controller was designed to calculate the additional yaw moment in the upper layer, and the sideslip angle was estimated by using the Unscented Kalman filter algorithm. In the lower layer, a torque optimal distribution algorithm was developed with the consideration of the motor limited condition and road adhesion constraint. Then the control strategy model was established and verified under double lane change and sine hysteresis condition in the co-simulation environment of Matlab/Simulink and Carsim. The simulation results indicate that the proposed control strategy, comparing with the uncontrolled condition, can well tracking the lane and improve the steering stability of vehicle.
Vehicle Parameters Estimation Under Braking and Steering Condition Based on EKF Observer
Authors: Tan Zi-Hu  , Gong Xian-Wu  , Zhang Yi-Xi  , Zhao Xuan
Published: February 2025

In order to estimate the parameters of the vehicle under cornering and steering conditions, the paper proposes two EKF-based observer models. The models consider the influence of the braking/driving force of each individual tire on the whole vehicle. For the purpose of improving the accuracy of the lateral force estimation, the lateral relaxation length is introduced and then observe the influence of relaxation length' change on observer through simulation. Finally, the estimated effect of the observers are verified by double lane-change test under the Co-simulation experiment of Carsim/Simulink. The simulation results show that the proposed method can effectively estimate the vehicle state parameters.
Some Highlights of Human Language Technology in Baltic Countries
Authors: Skadiņa Inguna
Published: February 2025

Today, when we are surrounded by different smart devices, life of our languages is very much influenced by technologies that support them in digital environment. Language technology solutions are particularly important for languages that are small in size. This paper aims to analyze representation of languages of Baltic countries – Estonian, Latvian and Lithuanian – in digital environment. We analyze technological challenges for these languages and most important achievements (recently created language resources and tools) that help to narrow technological gap with widely used languages, facilitate use of the natural language in interaction between computer and human, and minimize threat of digital extinction. Special attention is paid to the natural language understanding task, machine translation and speech technologies.
Smart City as a Platform-Based Ecosystem
Authors: Bajec Marko
Published: February 2025

While for a smart city there is no generally accepted definition, there exists a wide consensus of what a smart city (or country) should bring to its citizens. It is believed that it such smart environment, all required conditions are met for a quality of life of individuals and communities and for sustainable economic growth. In most circumstances, this is associated with the availability of health and social security, the ease of use of public services, efficient mobility, security, job and business opportunities etc. How to achieve that remains a challenge of the 21st century. In this paper, we describe a program of R&D projects that were launched in late 2016 within the Slovenian Smart Specialization initiative as a response to the aforementioned challenge.
Effectiveness of the Asynchronous Client-Side Coordination of Cluster Service Sessions
Authors: Petrauskas Karolis  , Baronas Romas
Published: February 2025

A system-to-system communication involving stateful sessions between a clustered service provider and a service consumer is investigated in this paper. An algorithm allowing to decrease a number of calls to failed provider nodes is proposed. It is designed for a clustered client and is based on an asynchronous communication. A formal specification of the algorithm is formulated in the TLA+ language and was used to investigate the correctness of the algorithm. An agent-based model was constructed and used to evaluate effectiveness of the proposed algorithm by performing simulations.
Effects of Telenursing Triage and Advice on Healthcare Costs and Resource Use
Authors: Gidora Hanne  , Borycki Elizabeth M.  , Kushniruk Andre W.
Published: February 2025

Telenursing triage and advice services are continuing to expand both nationally and internationally. A primary role of telehealth nursing triage is to channel patients or clients towards appropriate levels of care, thereby reducing healthcare costs and freeing up resources.
Data Migration from Operating EMRs to OpenEMR with Mirth Connect
Authors: Lin Jing  , Ranslam Kyle  , Shi Fang  , Figurski Mike  , Liu Zheng
Published: February 2025

Electronic medical records (EMR) are integral to the functionality of day to day operations in a clinic. EMRs perform functions like scheduling or hosting medical records used by physicians and other staff [1]. A certain time comes when it is necessary to upgrade or change EMRs to maintain efficiency in a clinic. The most arduous part of changing a clinic's EMR is migrating the clinical data from the old EMR to the new. This paper explores the feasibility of data migration between two Electronic Medical Records using open source technologies. This enables smaller clinics to change EMRs when the need arises without incurring huge costs. Using Mirth Connect as a data integration engine and OpenEMR as the new EMR we successfully migrated data from our old EMR to OpenEMR.
Modeling Keyword Search Strategy: Analysis of Pharmacovigilance Specialists' Search of MedDRA Terms
Authors: Marcilly Romaric  , Douze Laura  , Bousquet Cedric  , Pelayo Sylvia
Published: February 2025

In the information retrieval task, searching and choosing keywords to form the query is crucial. The present study analyzes and describes the keywords' search strategy into a thesaurus in the field of pharmacovigilance. Two ergonomics experts shadowed 22 pharmacovigilance specialists during their daily work. They focus on the strategies for searching and choosing MedDRA terms to build pharmacovigilance queries. Interviews of four pharmacovigilance specialists completed the observations. Results highlight that, for unusual or complex searches, pharmacovigilance specialists proceed iteratively in three main phases: (i) preparation of a list of terms and of evaluation criteria, (ii) exploration of the MedDRA hierarchy and choice of a term, and (iii) evaluation of the results against the criteria. Overall, the search and the choice of keywords within a thesaurus shares similarity with the information retrieval task and is closely interwoven with the query building process. Based on the results, the paper proposes design specifications for new interfaces supporting the identification of MedDRA terms so that pharmacovigilance reports searches achieve a good level of expressiveness.
Factors Associated with Increased Adoption of a Research Data Warehouse
Authors: Baghal Ahmad  , Zozus Meredith  , Baghal Amanda  , Al-Shukri Shaymaa  , Prior Fred
Published: February 2025

The increased demand of clinical data for the conduct of clinical and translational research incentivized repurposing of the University of Arkansas for Medical Sciences' enterprise data warehouse (EDW) to meet researchers' data needs. The EDW was renamed the Arkansas Clinical Data Repository (AR-CDR), underwent content enhancements, and deployed a self-service cohort estimation tool in late of 2016. In an effort to increase adoption of the AR-CDR, a team of physician informaticist and information technology professionals conducted various informational sessions across the UAMS campus to increase awareness of the AR-CDR and the informatics capabilities. The restructuring of the data warehouse resulted in four-fold utilization increase of the AR-CDR data services in 2017. To assess acceptance rates of the AR-CDR and quantify outcomes of services provided, Everett Rogers' diffusion of innovation (DOI) framework was applied, and a survey was distributed. Results show the factors that had impact on increased adoption were: presence of physician informaticist to mediate interactions between researchers and analysts, data quality, communication with and engagement of researchers, and the AR-CDR's team responsiveness and customer service mindset.
Challenges in Displaying Health Data on Small Smartwatch Screens
Authors: Neshati Ali  , Sakamoto Yumiko  , Irani Pourang
Published: February 2025

Using smartwatches for self-tracking purposes has become increasingly common. This tracking is possible as a result of the many sensors embedded in modern smartwatches including GPS, heart rate monitor, accelerometer, and gyroscope. The ability to obtain personal health-related data is one of the most compelling reason to purchase such devices. However, form factor limitations create numerous challenges for users hoping to access and interpret the data available. Typically, users rely on a secondary device, such as a smartphone to view health data. The aim of our research is to identify methods to improve user consumption of health-related data directly on a smartwatch. To study and apply novel visualization approaches, several key challenges need to be addressed. We present these here along with their corollary methods of circumvention.
Towards a Clinical Analytics Adoption Maturity Framework for Primary Care
Authors: Stoldt Jean-Philippe  , Price Morgan  , Weber Jens
Published: February 2025

Clinical decision support systems are evolving with growing analytics capabilities towards pervasive use of artificial intelligence. Maturity models can guide the adoption of these new technologies in clinical practice to improve patient outcomes in primary care settings. Our literature survey identified the “Health Analytics Adoption Maturity Model” by Canada Health Infoway as a suitable basis for developing an adoption maturity framework with primary care focus. We follow a design-science research paradigm to develop a scientifically-validated mixed-method approach for assessing and guiding the evolution of clinical analytics capabilities in primary care. This paper summarizes the first phase of our research in progress.
Describing Telenurses' Decision Making Using Clinical Decision Support: Influential Factors Identified
Authors: Tuden Danica S.  , Borycki Elizabeth M.  , Kushniruk Andre W.
Published: February 2025

Objective: Understand the cognitive processes of telenurses' decision making with the use of health information systems (HIS), specifically Clinical Decision Support Systems (CDSS). In addition, identify the factors that influence how telenurses use CDSS.
Nursing Informaticians Address Patient Safety to Improve Usability of Health Information Technologies
Authors: Williams Amy
Published: February 2025

With the introduction of Health Information technology, the potential for unintended consequences can occur. Island Health developed a Quality Assurance review process to evaluate and identify opportunities for system optimization, education and engagement, policy changes, as well as identify unintended consequences of Electronic Health Record (EHR) implementations. The Patient Safety Learning System was utilized to audit and evaluate reported safety events for system breaks and opportunities, practice and policy, as well as workflow implications. The findings were then reported to the reporter, leadership, and through governance structures. This process identified that 242 reported patient safety events in 1 year has resulted in 30 (13.7%) of these events leading to EHR System optimization. Ultimately Island Health's Nurse Informaticists foster a culture of safety through their QA/QI Patient Safety event investigations which improve system usability and ultimately Patient Safety.
Training as an Intervention to Decrease Medical Record Abstraction Errors Multicenter Studies
Authors: Zozus Meredith Nahm  , Young Leslie W.  , Simon Alan E.  , Garza Maryam  , Lawrence Lora  , Ounpraseuth Songthip T.  , Bledsoe Megan  , Newman-Norlund Sarah  , Jarvis J. Dean  , McNally Mary  , Harris Kimberly R.  , McCulloh Russell  , Aikman Rachel  , Cox Sara  , Malloch Lacy  , Walden Anita  , Snowden Jessica  , Chedjieu Irene Mangan  , Wicker Chester A.  , Atkins Lauren  , Devlin Lori A.
Published: February 2025

Studies often rely on medical record abstraction as a major source of data. However, data quality from medical record abstraction has long been questioned. Electronic Health Records (EHRs) potentially add variability to the abstraction process due to the complexity of navigating and locating study data within these systems. We report training for and initial quality assessment of medical record abstraction for a clinical study conducted by the IDeA States Pediatric Clinical Trials Network (ISPCTN) and the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) Neonatal Research Network (NRN) using medical record abstraction as the primary data source. As part of overall quality assurance, study-specific training for medical record abstractors was developed and deployed during study start-up. The training consisted of a didactic session with an example case abstraction and an independent abstraction of two standardized cases. Sixty-nine site abstractors from thirty sites were trained. The training was designed to achieve an error rate for each abstractor of no greater than 4.93% with a mean of 2.53%, at study initiation. Twenty-three percent of the trainees exceeded the acceptance limit on one or both of the training test cases, supporting the need for such training. We describe lessons learned in the design and operationalization of the study-specific, medical record abstraction training program.
Applying the Behavior Change Technique Taxonomy to Mobile Health Applications: A Protocol
Authors: Courtney Karen L.  , Antonio Marcy  , Garnett Ashley  , Matthews Judith T.
Published: February 2025

The lack of standardized descriptors of behavior change facilitators in mobile health apps makes it difficult for clinicians and consumers to quickly evaluate the potential of a mobile health app. The Behavior Change Technique Taxonomy (BCTT) was developed to evaluate health interventions for the presence of behavior change techniques. This paper describes the methods used and methodological results in applying the BCTT to commercially available mobile health apps in the respiratory and sleep domains.
Philosophy and the Ontologies of Knowledge Representation in AI
Authors: Giaretta Pierdaniele
Published: February 2025

Firstly, philosophy and science are compared by taking into account five aspects: critical attitude towards the assumptions, definitions and terminological rigor, formulation of a theory and its inferential development, control and external support, presence of a holistic approach. Secondly, for each aspect, some reasons that make the ontologies of Knowledge Representation closer to philosophy or closer to science are pointed out. Conclusions are different and not clear-cut. In the discussion of the fifth aspect Nicola Guarino's approach is emphasized and presented in the light of Carnap's notion of explication.
Privacy by Design for Integrated Case and Care Management: Receiver-Oriented Encryption in STROKE OWL
Authors: Michelsen Timo  , Lins Christian  , Gudenkauf Stefan  , Hein Andreas  , Lüpkes Christian
Published: February 2025

Research into new forms of care for complex chronic diseases requires substantial efforts in the collection, storage, and analysis of medical data. Additionally, providing practical support for those who coordinate the actual care management process within a diversified network of regional service providers is also necessary. For instance, for stroke units, rehabilitation partners, ambulatory actors, as well as health insurance funds. In this paper, we propose the concept of comprehensive and practical receiver-oriented encryption (ROE) as a guiding principle for such data-intensive, research-oriented case management systems, and illustrate our concept with the example of the IT infrastructure of the project STROKE OWL.
Interoperability Improvement of Mobile Patient Survey (MoPat) Implementing Fast Health Interoperability Resources (FHIR)
Authors: Storck Michael  , Hollenberg Luca  , Dugas Martin  , Soto-Rey Iñaki
Published: February 2025

Despite the advances in health information technology and the increasing usage of electronic systems, syntactic and semantic interoperability between different health information systems remains challenging. An emerging standard to tackle interoperability issues is HL7 FHIR, which uses modern web technologies for communication like Representational State Transfer. The electronic patient reported outcome system Mobile Patient Survey (MoPat) was adapted to support metadata import and clinical data export using HL7 FHIR. Thereby, the data models of HL7 FHIR and MoPat were compared and the existing import and export functions of MoPat were extended to support HL7 FHIR. A test protocol including eight test datasets to proof functioning of the new features was successfully conducted. In the near future, a real time searching toolbar of FHIR metadata resources will be integrated within MoPat. MoPat FHIR import and export functions are ready to be used in a clinical setting in combination with a FHIR compliant clinical data server.
Implementing LOINC: Current Status and Ongoing Work at the Hannover Medical School
Authors: Fiebeck Johanna  , Gietzelt Matthias  , Ballout Sarah  , Christmann Martin  , Fradziak Maikel  , Laser Hans  , Ruppel Julia  , Schönfeld Norman  , Teppner Sonja  , Gerbel Svetlana
Published: February 2025

The Logical Observation Identifiers, Names and Codes (LOINC) is a common terminology used for standardizing laboratory terms. Within the HiGHmed consortium, LOINC is used as a central terminology for health data sharing across all university hospital sites. Therefore, linking the LOINC codes to the site-specific tests and measures is one crucial step to reach this goal. In this work we report our ongoing work in implementing LOINC to the laboratory information system, our challenges and lessons learned.
Analysis of Primary Care Computerised Medical Records with Deep Learning
Authors: de Lusignan Simon  , Smith Nadia  , Livina Valerie  , Yonova Ivelina  , Webb Rebecca  , Thomas Spencer A.
Published: February 2025

The analysis of primary care data plays an important role in understanding health at an individual and population level. Currently the utilization of computerized medical records is low due to the complexities, heterogeneities and veracity associated with these data. We present a deep learning methodology that clusters 11,000 records in an unsupervised manner identifying non-linear patterns in the data. This provides a useful tool for visualization as well as identify features driving the formation of clusters. Further analysis reveal the features that differentiate sub-groups that can aid clinical decision making. Our results uncover subsets that contain the highest proportion of missing data, specifically Episode type, as well as the sources that provide the most complete data.
Towards a Software Tool for Planning IHE-Compliant Information Systems
Authors: Stäubert Sebastian  , Strübing Alexander  , Drepper Johannes  , Bergh Björn  , Winter Alfred  , Merzweiler Angela
Published: February 2025

As hospital information systems are complex and the requirements for interoperability grow with the increasing networking in healthcare, careful planning becomes more and more necessary. The use of standards as described in IHE profiles, for example, are an important prerequisite for enabling interoperability. Enterprise Architecture Planning (EAP) methods should support this, but none of the currently available EAP methods offers the option of using IHE profiles. The 3LGM2IHE project wants to close this gap and implement the support of IHE profiles in the 3LGM2tool. This paper describes how requirements for this tool were determined and presents the results.
Streamlining Hospital IT – Improving the Admission Process
Authors: Holm Jürgen  , Kammermann Fabian  , Noser Philipp  , Sariyar Murat  , Bürkle Thomas
Published: February 2025

We analyzed the admission workflow in three Swiss hospitals of different size for normal and emergency admissions. Our goal was to detect shortcomings mainly in the administrative admission process due to media breaks. We obtained 9 different workflows (three per hospital) and a total of 22 shortcomings in the admission process which were present or likely in two or more of the hospitals. A considerable number could be traced back to missing information requiring time consuming extra work. We drafted five potential IT-based workflow changes and made, together with the hospital partners, a cost-benefit analysis which solution would be most interesting. As a result, a concept for an open multi center hospital admission portal was drafted, which, in theory, should influence 8 of the 22 problems found. Specifically, the prototype of the portal was designed for a direct triangular interaction between the referring doctor, the patient and the hospital staff.
Can the Austrian Nation-Wide EHR System Support the Recruitment of Trial Patients?
Authors: Augustinov Gabriela  , Duftschmid Georg
Published: February 2025

Automatic comparison of routinely collected EHR data with trial eligibility criteria can speed up patient recruitment. The present work aims to analyze to what extent the Austrian nation-wide EHR system ELGA could support this task. Using the open source tool ART-DECOR we tried to map a reference list of 150 common eligibility criteria specified in the EHR4CR project to the HL7 CDA templates that describe the structure of ELGA document types. For 61% of the criteria mappings could be made to ELGA template elements holding structured data. Comparing our results with similar work, we conclude that ELGA could be a useful component for the automatic identification of trial patients.
Ensemble Based Approach for Time Series Classification in Metabolomics
Authors: Netzer Michael  , Hanser Friedrich  , Breit Marc  , Weinberger Klaus M.  , Baumgartner Christian  , Baumgarten Daniel
Published: February 2025

Background: Machine learning is one important application in the area of health informatics, however classification methods for longitudinal data are still rare.
A Multi-Criterial Support Tool for the Multimorbidity Decision in General Practice
Authors: Rajput Vije Kumar  , Kaltoft Mette Kjer  , Dowie Jack
Published: February 2025

The magnitude and seriousness of the challenge posed by heterogeneous multimorbidity in most health services is now unquestioned. Equally well-acknowledged is the fact that existing guidelines essentially set out the principles of best practice in an idealised setting, concentrating on information gathering and not providing any personalisable decision support for the general practitioner aiming to share decision making with a person with multiple morbidities in the reality of routine practice. Existing decision aids have been developed largely within the single condition context and can draw on a body of robust research largely absent in the multimorbidity context. The need for a more flexible and generic approach which draws more on the clinician's expertise-based judgments has been called for, and we introduce a Decision Support Tool, GREST CLIN, in response to this call. Based on Multi-Criteria Decision Analysis it reflects the quantitative calculation approach to decision support rather than the deliberative reasoning of mainstream decision aids. It is emphasised that any evaluation should use the current decision making process as empirical comparator, rather than idealised normative standards, and that the primary outcome measure should be decision quality at the point of care, not downstream outcomes. A demonstration version of the tool is available online as proof of method.
Healthcare Staffs' Information Security Practices Towards Mitigating Data Breaches: A Literature Survey
Authors: Yeng Prosper Kandabongee  , Yang Bian  , Snekkenes Einar Arthur
Published: February 2025

The purpose of this study was to understand healthcare staffs' information security (IS) practices towards mitigating data breaches. A literature survey was conducted to understand the state-of-the-art methods, tools, evaluation techniques and the challenges to their implementation. The results would be used for emperical studies in a hospital setting in Norway on Healthcare Security Practice Analysis, Modeling and Incentivization (HSPAMI). Human Aspect of Information Security Questionnaire was identified as robust and comprehensive tool for gathering staff security practices. Integrated theories was being adopted to form a comprehensive staffs' characteristics. A mixed-method for evaluating the theories was also identified to be the best strategy.
In-Vehicle Respiratory Rate Estimation Using Accelerometers
Authors: Wang Ju  , Warnecke Joana M.  , Deserno Thomas M.
Published: February 2025

The monitoring of vital signs in a dynamic environment is challenging. This work demonstrates an approach to estimate the respiratory rate (RR) under real-driving conditions by using two accelerometers for signal recording and de-noising. One accelerometer was attached to the seatbelt for recording respiratory movements; another one was attached to the left side of the car seat for recording noise. The frequency components of the noise were used to suppress the noise hidden in the signal. The performance of the proposed approach is evaluated for three testers under three driving conditions, i.e., engine on, flat road and uneven road. The estimated RRs for three testers are 11.54 ± 2.28 breaths per minute (bpm), 15.57 ± 5.77 bpm, and 9.63 ± 4.58 bpm. The median estimated RR for three testers are 12.08 bpm, 18.26 bpm, and 7.76 bpm, where the manually counted reference RRs are 12 bpm, 18 bpm, and 7 bpm respectively. The average difference between estimated RRs and reference RRs is 0.71 bpm for the condition engine on, 3.36 bpm for flat road, and 4.58 bpm for uneven road. The results exhibit the ability of the proposed approach to estimate RR under real-driving conditions.
Pengaruh Harga Bitcoin dan Kurs Poundsterling Terhadap Harga Kontrak Futures Emas
Authors: Arif Surahman  , Nani Rusnaeni
Published: February 2025

Penelitian ini bertujuan untuk mengeksplorasi pengaruh fluktuasi harga Bitcoin dan kurs Poundsterling terhadap harga kontrak futures emas. Fluktuasi harga emas dipengaruhi oleh banyak faktor, termasuk perubahan nilai tukar mata uang dan pergerakan harga Bitcoin, yang semakin dikenal sebagai "emas digital". Penelitian ini menggunakan metode regresi kuantil untuk menganalisis data sekunder yang diambil dari situs web terkait, termasuk harga kontrak futures emas, Bitcoin, dan kurs Poundsterling terhadap dolar AS. Hasil analisis menunjukkan bahwa fluktuasi harga Poundsterling memberikan pengaruh signifikan terhadap harga kontrak futures emas di semua kuantil yang diuji, sementara fluktuasi harga Bitcoin hanya memberikan pengaruh signifikan pada kuantil median. Oleh karena itu, dapat disimpulkan bahwa perubahan harga Poundsterling memiliki pengaruh yang lebih besar dan konsisten terhadap harga emas dibandingkan dengan Bitcoin, yang pengaruhnya terbatas pada beberapa kuantil tertentu. Penelitian ini memberikan wawasan penting bagi investor yang ingin mengelola portofolio investasi dalam emas dengan mempertimbangkan pergerakan mata uang besar seperti Poundsterling.