bluuebunny/crossref_metadata_2025 huggingface dataset:
Supervised Analysis of Drug Prescription Sequences
Authors: Ficheur Grégoire  , Chazard Emmanuel  , Merlin Béatrice  , Ferret Laurie  , Luyckx Michel  , Beuscart Régis
Published: February 2025

Hospitals have at their disposal large databases that may be considered for reuse. The objective of this work is to evaluate the impact of a drug on a specific laboratory result by analyzing these data. This analysis first involves building a record of temporal patterns, including medical context, of drug prescriptions. Changes in outcome due to these patterns of drug prescription are assessed using short phases of the inpatient stay compared to monotonous changes in the laboratory result. To illustrate this technique, we investigated potassium chloride supplementation and its impact on kalemia. This method enables us to assess the impact of a drug (in its frequent context of prescription) on a laboratory result. This kind of analysis could play a role in post-marketing studies.
An Evaluation Framework and A Pilot Study of a Mobile Platform for Diabetes Self-Management: Insights from Pediatric Users
Authors: Padman Rema  , Jaladi Sravani  , Kim Sean  , Kumar Saumitra  , Orbeta Philip  , Rudolph Kate  , Tran Tony
Published: February 2025

According to WHO, pediatric diabetes is a rising global public health problem, with increasing impact on developing nations. This study summarizes a multidimensional, scalable pilot evaluation of a diabetes self-management platform combining mobile technology with social networking to capture four key metrics of Type 1 diabetes self-management, associated social interactions, and gaming features providing targeted feedback to 8 pediatric users. Based on their 2-month interaction with the application, we analyze click-stream data from social interactions, key health metrics, text comments, and usability and satisfaction surveys to evaluate engagement with the platform and effectiveness in controlling blood glucose using a product-process-program framework. Our preliminary results indicate that this framework was successful in demonstrating the potential of the mobile health platform to effectively leverage the growing use of mobile applications and social media to present a unique benefit that engaged pediatric users and provided useful insights for self-health management.
Missed Opportunities Mapping: Computable Healthcare Quality Improvement
Authors: Brown Benjamin  , Williams Richard  , Ainsworth John  , Buchan Iain
Published: February 2025

Introduction: Analysing variance from care pathways in situations when adverse health outcomes have occurred may identify missed opportunities for healthcare improvement.
Design of Schistosomiasis Ontology (IDOSCHISTO) Extending the Infectious Disease Ontology
Authors: Camara Gaoussou  , Despres Sylvie  , Djedidi Rim  , Lo Moussa
Published: February 2025

Epidemiological monitoring of the schistosomiasis' spreading brings together many practitioners working at different levels of granularity (biology, host individual, host population), who have different perspectives (biology, clinic and epidemiology) on the same phenomenon. Biological perspective deals with pathogens (e.g. life cycle) or physiopathology while clinical perspective deals with hosts (e.g. healthy or infected host, diagnosis, treatment, etc.). In an epidemiological perspective corresponding to the host population level of granularity, the schistosomiasis disease is characterized according to the way (causes, risk factors, etc.) it spreads in this population over space and time. In this paper we provide an ontological analysis and design for the Schistosomiasis domain knowledge and spreading dynamics. IDOSCHISTO – the schistosomiasis ontology – is designed as an extension of the Infectious Disease Ontology (IDO). This ontology aims at supporting the schistosomiasis monitoring process during a spreading crisis by enabling data integration, semantic interoperability, for collaborative work on one hand and for risk analysis and decision making on the otherhand.
A Study of Information Management in the Patient Surgical Pathway in NHSScotland
Authors: Bouamrane Matt-Mouley  , Mair Frances S.
Published: February 2025

We conducted a study of information management processes across the patient surgical pathway in NHSScotland. While the majority of general practitioners (GPs) consider electronic medical records systems as an essential and integral part of their work during the patient consultation, many were not fully satisfied with the functionalities of these systems. A majority of GPs considered that the national eReferral system streamlined referral processes. Almost all GPs reported marked variability in the quality of discharge information. Preoperative processes vary significantly across Scotland, with most services using paper-based systems. Insufficient use is made of information provided through the patient electronic referral leading to a considerable duplication of tasks already performed in primary care. Three health-boards have implemented electronic preoperative information systems. These have transformed clinical practices and facilitated communication and information-sharing among the multi-disciplinary team and within the health-boards. Substantial progress has been made towards improving information transfer and sharing within the surgical pathway in recent years. However, there remains scope for further improvements at the interface between services.
User Experience of interRAI Assessment Tools in New Zealand
Authors: Smith Joanne  , Whiddett Dick  , Hunter Inga
Published: February 2025

The international residential assessment instrument (interRAI) has been adopted for phased national implementation in New Zealand. It targets people over 65 years who require needs assessment for access to long term publicly funded services. There is limited research on the barriers to adoption for interRAI electronic assessment tools, and none relating to the New Zealand health sector. This research qualitatively explored clinicians' perceptions and experience of using interRAI electronic assessment tools using semi-structured interviews guided by constructs from the Unified Theory of Acceptance and Use of Technology (UTAUT) model [9]. Analysis was conducted using thematic analysis. Three major barriers to adoption of interRAI tools emerged from the research: 1) lack of ready access to individual laptops/computers with consistent network connectivity, 2) need for ongoing training for interRAI assessors, and, 3) lack of understanding of what information is being collected and for what reasons. The growth in aging populations will see greater use of interRAI electronic assessment tools, and therefore more clinicians required to learn and use the technology. Addressing these barriers to adoption is therefore vital.
AccessMRS: Integrating OpenMRS with Smart Forms on Android
Authors: Fazen Louis E.  , Chemwolo Benjamin T.  , Songok Julia J.  , Ruhl Laura J.  , Kipkoech Carolyne  , Green James M.  , Ikemeri Justus E.  , Christoffersen-Deb Astrid
Published: February 2025

We present a new open-source Android application, AccessMRS, for interfacing with an electronic medical record system (OpenMRS) and loading ‘Smart Forms’ on a mobile device. AccessMRS functions as a patient-centered interface for viewing OpenMRS data; managing patient information in reminders, task lists, and previous encounters; and launching patient-specific ‘Smart Forms’ for electronic data collection and dissemination of health information. We present AccessMRS in the context of related software applications we developed to serve Community Health Workers, including AccessInfo, AccessAdmin, AccessMaps, and AccessForms. The specific features and design of AccessMRS are detailed in relationship to the requirements that drove development: the workflows of the Kenyan Ministry of Health Community Health Volunteers (CHVs) supported by the AMPATH Primary Health Care Program. Specifically, AccessMRS was designed to improve the quality of community-based Maternal and Child Health services delivered by CHVs in Kosirai Division. AccessMRS is currently in use by more than 80 CHVs in Kenya and undergoing formal assessment of acceptability, effectiveness, and cost.
Computer-aided Treat to Target (T2T) Approach for the Rheumatology Patient
Authors: Gogia Shashi Bhushan  , Malaviya Anand
Published: February 2025

Since 2001,we had been using a document template with manual calculators to assess the disease status during each visit and based on that, formulate a proper treatment plan for our patients We had good outcomes but the process was laborious and slow. From 2007 onwards, we shifted to a rheumatology specific EMR with automatic calculators.
Future Challenges of Biomedical Informatics for Translational Medicine
Authors: López-Alonso Victoria  , Hermosilla-Gimeno Isabel  , López-Campos Guillermo  , Angel Mayer Miguel  , INBIOMEDvision Consortium
Published: February 2025

There are many challenges for Biomedical Informatics (BMI) to meet the promises of Translational Medicine. Several of the challenges have to do with the re-use of clinical data to progress towards 4P Medicine (personalized, preventive, participatory and predictive) and using epidemiology and clinical research as well as the translation of data and knowledge obtained in the laboratory into useful information for the clinical setting. The INBIOMEDvision EU funded project tackled these challenges in a series of events with expert scientists in different related disciplines. As a result, some consensus ideas were reached about the BMI challenges in the research areas of Genotype-Phenotype integration, Translational Systems Biology and Re-use of Clinical information in the Electronic Health Records (EHR) for research and what is needed to meet them.
Hospital Information System Survey in Qatar
Authors: Al-Ali Rashid  , Reti Shane  , Feldman Henry  , Safran Charles  , Niaz Rashid  , Erskine Alistair  , Elmagarmid Ahmed  , Al-Musleh Abdulwahab
Published: February 2025

Healthcare can be enhanced by the effective use of information technology to improve the quality and safety of care and many healthcare providers are adopting advanced health information technology to improve their healthcare delivery process. Qatar is a relatively young Middle Eastern country with an ambitious and progressive national strategy to develop its healthcare system, including an advanced e-health infrastructure delivering the right medical information at the right time to clinicians and patients. To assess the effectiveness of such programs, it is important to have a pre-intervention baseline from which comparisons, performance against target measures and forward thinking strategic planning can be grounded. This study presents the first published campus wide survey of Hospital Information Systems in large public and private hospitals in Qatar. Objective: To qualitatively assess and describe the current state of Hospital Information Systems in large hospitals in Qatar, and to establish a baseline or reference point for Qatar's readiness for, and adoption of Hospital Information Systems.
Our Health Language and Data Collections
Authors: Hovenga Evelyn J.S.  , Grain Heather
Published: February 2025

All communication within the health industry is dependent upon the use of our health language consisting of a very extensive and complex vocabulary. Converting this language into computable formats is necessary in a digital environment with a strong reliance on data, information and knowledge sharing. This chapter describes our health language, what terminologies and ontologies are, their use and relationships with natural language, indexing, data standards, data collections and the need for data governance.
Essential Questions: Accuracy, errors and user perceptions in a drag/drop user-composable Electronic Health Record
Authors: Senathirajah Yalini  , Kaufman David  , Bakken Suzanne
Published: February 2025

In previous work we have described the creation and user testing of a drag/drop user-composable electronic health record, MedWISE. Any new design poses new potential problems; here we discuss the accuracy, potential for new types of errors, and user reactions to the approach, including their perceptions of ease of use and usefulness. Our results come from a mixed methods laboratory study with 18 clinicians at a large academic medical center. 12 used MedWISE and 6 used the conventional system. MedWISE users had comparable assessment accuracy to use of the conventional system, low (1/10) risk of diagnosis momentum error, and overall favorable and even enthusiastic user perception. 10/12 said the system eased their cognitive process, Ease of use and usefulness were rated 3.79 and 4.00 on a 5-point Likert scale. Users were unconcerned about the possibility of increased errors due to their trust in colleagues and system similarities to current practice. After first describing the issues, we suggest a method to elucidate risks in innovative and current systems.
A Design to Empower Patients in Long Term Wellbeing Monitoring and Chronic Disease Management in mHealth
Authors: Li Yunqiu  , Owen Tom  , Thimbleby Harold  , Sun Na  , Rau Pei-Luen Patrick
Published: February 2025

With the growing population with chronic disease in most developed countries, the amount and variety of interactive medical devices adopted in healthcare and wellbeing management is on the rise. Studies show that people with chronic conditions are facing many barriers to effective self-management, which leads to significant economic losses in many countries. The question as to how we can design personal medical devices that are able to facilitate an effective self-management by tackling these barriers presents a challenging research topic. We offer an overview of a controlled-experiment designed to evaluate an innovative tagging feature and a confidence of measurement feature in chronic disease management. This is a work-in-progress, which will finish by the end of June 2013.
A Novel System for Customer Needs Management in Product Development
Authors: Chang Wunching  , Chen Chun-Hsien  , Chen Xingyu
Published: February 2025

Understanding and fulfilling each individual customer's needs has been recognized as a great challenge for companies across industries. Customer needs management, which is essentially concerned with the relationship between customer needs in the customer domain and product specifications or function requirements in the product domain, needs to be well addressed in the product development process. However, there is a lack of effective knowledge-based techniques supporting the implementation of a customer needs management system to obtain accurate customer needs statements. In this paper, a customer needs management system (CNMS) that combines the ontology customer needs representation (OCNR) system with the Involvement/Thinking/Feeling (ITF) customer segmentation model is presented to obtain accurate customer needs statements. Through classifying different types of customers based on innovative characteristics, acquiring customer needs by involving the identified innovative customers and using the obtained customer needs to generate more accurate needs statements. The detailed process of overall system implementation was presented. System evaluations, including terminology evaluation and high level needs statements evaluation, were conducted. Results and findings from the customer needs management system implementation were also discussed and summarized.
The Architecture of a Churn Prediction System Based on Stream Mining
Authors: Balle Borja  , Casas Bernardino  , Catarineu Alex  , Gavaldà Ricard  , Manzano-Macho David
Published: February 2025

Churning is the movement of customers from a company to another. For any company, being able to predict with some time which of their customers will churn is essential to take actions in order to retain them, and for this reason most sectors invest substantial effort in techniques for (semi) automatically predicting churning, and data mining and machine learning are among the techniques successfully used to this effect. In this paper we describe a prototype for churn prediction using stream mining methods, which offer the additional promise of detecting new patterns of churn in real-time streams of high-speed data, and adapting quickly to a changing reality. The prototype is implemented on top of the MOA (Massive Online Analysis) framework for stream mining. The application implicit in the prototype is the telecommunication operator (mobile phone) sector.
Automatic Trend Line Generation for Time-Series Analysis: A Graphical Approach
Authors: Rivera Peruyero Juan Ricardo  , Marti-Puig Pere
Published: February 2025

Trend lines are revealed useful to explain the past evolution of time-series of prices that are represented on graphics. However, in practice, there are a huge amount of possible trend lines to be plotted but only a reduced set of them are significant or relevant. The rapid identification of relevant trend lines when they are in their initial phase of their development could provide interesting projections for the future evolution of time-series. This approach is focused on the graphical analysis of time-series –especially those coming from financial asset prices– under a framework of trend lines.
Reasoning about Human Activities: an Argumentative Approach
Authors: Nieves Juan Carlos  , Guerrero Esteban  , Lindgren Helena
Published: February 2025

Recognizing and supporting human activities is an important challenge for ambient assisted living. In this paper we introduce a novel argumentation-based approach for dealing with human activity recognition. By considering a model of the world and a set of observations of the world, hypothetical fragments of activities are built. The hypothetical fragments of activities will be goal-oriented actions and they will be considered defeasible. Therefore we consider extension-based argumentation semantics for local selection of hypothetical fragments of activities. By considering degrees of fulfillment of activities and local selection, a global selection of hypothetical fragments of the activities is defined. Therefore, we can make explicit statements about why one hypothetical activity was performed.
Query-Focused Association Rule Mining for Information Retrieval
Authors: Sizov Gleb  , Öztürk Pinar
Published: February 2025

We present a method that applies association rule mining for information retrieval. Our approach is different from traditional information retrieval since retrieval is done based on association rather than similarity, which might be useful for knowledge discovery purposes such as finding an explanation or elaboration for an event in a collection of domain-specific documents. The method proposed in this paper is based on the SmoothApriori algorithm which accommodates similarity in the association rule mining process to mine association rules between sentences or larger text units. We introduce query-focused association rule mining that allows association-based retrieval from larger amount of data than with a traditional association-rule mining approach. Combined with SmoothApriori, query-focused association rule mining provides association-based retrieval for textual data. This new method was evaluated on the task of automatically restoring sentences that were artificially removed from aviation investigation reports and showed significantly better results than any of our similarity-based retrieval baselines.
On Programming Organization-Aware Agents
Authors: Jensen Andreas Schmidt
Published: February 2025

Since it is difficult (or even impossible) to assume anything about the agents' behavior and goals in an open multi-agent system, it is often suggested that an organization is imposed upon the agents, whichhich, by abstracting away from the agents, specifies boundaries and objectives that the agents, by enacting roles, are expected to adhere to. In practice, this is usually done by creating a middleware, which acts as a bridge between an organizational specification and the agents, often taking away too much of the agents' autonomy. This project investigates how to make agents organization-aware, thus removing the middleware and letting the agents directly reason about the organization. In this paper, we discuss the results so far, and describe the future goals and research direction for the project.
Industrial Robot Skills
Authors: Stenmark Maj
Published: February 2025

When robots are working in dynamic environments, close to humans lacking extensive knowledge of robotics, there is a strong need to simplify the user interaction and make the system execute as autonomously as possible. For industrial robots working side-by-side with humans in manufacturing industry, AI systems are necessary to lower the demand on programming time and expertise. One central concept in knowledge modeling for robots is action representation. In this paper, we describe our representation of robot skills. The skills have resource requirements, logical and procedural information from which executable code can be generated.
On deriving semantic representations from dependencies: A Practical approach for evaluating meaning in learner corpora
Authors: Hahn Michael  , Meurers Detmar
Published: February 2025

One of the reasons for the popularity of dependency approaches in recent computational linguistics is their ability to efficiently derive the core functor-argument structure of a sentence as an interface to semantic interpretation. Exploring this feature of dependency structures further, in this paper we show how basic dependency representations can be mapped to semantic representation as used in Lexical Resource Semantics, an underspecified semantic formalism originally developed as a semantic formalism for the HPSG framework and its elaborate syntactic representations. We describe a two stage process, which in the first stage establishes a syntax-semantics interface representation abstracting away from some differences in surface dependencies. It ensures the local reconstruction of arguments for middle and long-distance dependencies, before building the actual LRS semantics in the second stage. We evaluate the approach on the CREG-109 corpus, a small dependency-annotated corpus with answers to reading comprehension questions written by American learners of German.
From Oral Hearing to Opinion in the U.S. Supreme Court
Authors: Al-Abdulkarim Latifa  , Atkinson Katie  , Bench-Capon Trevor
Published: February 2025

In this paper we provide a structured analysis of US Supreme Court Oral Hearings to enable identification of the relevant issues, factors and facts that can be used to construct a test to resolve a case. Our analysis involves the production of what we term ‘argument component trees’ (ACTs) in which the issues, facts and factors, and the relationship between these, are made explicit. We show how such ACTs can be constructed by identifying the speech acts that are used by the counsel and Justices within their dialogue. We illustrate the application of our analysis by applying it to the oral hearing that took place for the case of Carney v. California, and we relate the majority and minority opinions delivered in that case to our ACTs. The aim of the work is to provide a formal framework that addresses a particular aspect of case-based reasoning: enabling the identification and representation of the components that are used to form a test to resolve a case and guide future behaviour.
Classification of Regulatory Paragraphs by Discourse Structure, Reference Structure, and Regulation Type
Authors: Buabuchachart Alan  , Metcalf Katherine  , Charness Nina  , Morgenstern Leora
Published: February 2025

As part of a larger effort to explore the feasibility of automating the translation of regulatory text to formal, executable rules, we have developed automated methods to classify regulatory paragraphs into various categories of interest, including regulation type and reference structure. We achieve F1 scores of at least .8 for most categories.
Icon Representations in Supporting Requirements Elicitation Process
Authors: Khanom Sukanya  , Heimbürger Anneli  , Kärkkäinen Tommi
Published: February 2025

This paper considers the difficulties faced by the stakeholders in general requirements engineering (RE). These difficulties range from the complexity of requirements gathering to requirements presentation. Affordable visualization techniques have been widely implemented to support the requirements engineering community. However, no universal characteristics that could be associated with requirements completion have been identified so far. The research focus of this paper is driven by the above considerations to introduce the icon-based language comprising a set of icon notations, syntactic and semantics. Icon-based language would support the requirements engineering tasks that normally executed by stakeholders and provide a visual modelling language to unify the requirement activities. Research approach is recapitulate, firstly, by identifying the requirements engineering artefact, secondly by refining the icon artefact, and thirdly, by integrating those two artefacts by means of requirements engineering process. The result aimed at to make communications more interactive and manageable by facilitating the exchange of information and to promote global understanding in any requirements development context across cultural and national boundaries.
Categories for Description of Reference Models
Authors: Torge Sunna  , Esswein Werner  , Lehrmann Sina  , Thalheim Bernhard
Published: February 2025

Conceptual modeling is fundamental within information system engineering. However, it is still difficult to share models, to find reference models or to reuse suitable existing models. Motivated by the Open Model Initiative this paper presents a Meta Modeling Framework for the description of reference models in order to support both common use of existing models and development of new models. This work targeted to specify significant categories and attributes that allow representing knowledge about reference models with an appropriate abstraction level and granularity. The methodological approach and the framework are presented and design decisions are discussed. The usage of the framework is exemplarily sketched.
Multi-Dimensional Schema Composition for Conceptual Modelling in the Large
Authors: Noack René  , Thalheim Bernhard
Published: February 2025

Conceptual modelling has been changed over years. Nowadays conceptual modelling in the small has become state of the art for specialists and educated application engineers. Conceptualisations have been developed for almost any aspect of an information system (structuring, functionality, interactivity, distribution, architectural components), for most of the implementation decisions such as tuning or performance improvement, for many facets or viewpoints on the application domain etc. The area of conceptual modelling became a science for typical small-range applications with small schemata. Large schemata typically grow incrementally or are a result of migration or integration of schemata or are obtained after consolidation of applications. Typical industrial applications such as SAP R/3 use thousands or tens of thousands database types and have schemata that are not easy to handle, to maintain, to evolve or to map to logical or physical languages at the implementation level. Conceptualisation in the large is typically performed by many modelers and teams. It also includes architectural aspects within applications. At the same time quality, configuration and versioning of models developed so far become an issue.
Logical Specification of Processes
Authors: Číhalová Martina  , Duží Marie  , Menšík Marek
Published: February 2025

In the last decades we got used to software applications (or computers, if you like) being everywhere and working for us. Yet sometimes they fail to work as desired. The current situation is often characterized as the second software crisis. There are many alleged causes of this state. They include, inter alia, web net overload, loss of data, inconsistency of data, intrusions by hackers, etc. etc. Yet in our opinion, the main problem is an old one. It consists in an insufficient specification of the procedures to be executed. We have been dealing with this problem since the beginning of computer era. Though there are many specification methods and languages, the problem remains very much a live issue and so far no satisfactory solution has been found. Our stance is that a declarative logical specification is needed. A serious candidate for such a high-quality declarative specification is a higher-order logic equipped with a procedural semantics. The goal of our contribution is to describe a specification method using Transparent Intensional Logic (TIL). TIL is a hyperintensional, typed, partial lambda-calculus. Hyperintensional, because the meaning of TIL-terms are not the functions/mappings themselves; rather, they are procedures producing functions as their products. Proper typing makes it possible to define inputs and outputs of a procedure. Finally, we must take into account partiality and the possibility of a failure to produce a product. A procedure may fail to produce a correct product for one of two reasons. Either the mapping the procedure produces is undefined at the argument(s) serving as point(s) of evaluation, or the procedure is ill- or under-specified, in which case the empirical execution process has undesirable results. This paper investigates, in a logically rigorous manner, how a detailed specification can prevent these problems.
3D Simulation of a Hospital Environment and Ward Round to Augment a Summer School Program for Pre-Medical Students
Authors: Kulendran Myutan  , Taylor Michael  , Taylor David  , Darzi Ara
Published: February 2025

Students applying to medical school may benefit from a better understanding of the clinical environment and the duties of a doctor. Despite attachments at hospital they may feel detached from the decision making process which is a pivotal part of being a clinician. A simulated hospital environment was tried on 30 pre-med students from an urban environment to test the feasibility of using structured clinical scenarios to augment their experience of a clinical setting.
An Ultrasound-Based Navigation System for Minimally Invasive Neck Surgery
Authors: Brennecke Thorsten  , Jansen Nils  , Raczkowsky Joerg  , Schipper Joerg  , Woern Heinz
Published: February 2025

Future minimally invasive neck surgery requires a navigation system adapted to the actual intra-operative bedding of the patient. The detection of the bedding-caused tissue shift is essential for a safe orientation for the surgeon new endoscopic operation procedures in neck surgery. It is essential to visualize the relation between important anatomic landmarks and operation instruments at any time. Within the scientific project SACAS we focus on developing an ultrasound supported navigation system based on preoperative imaging which considers the intra-operative tissue shift. A rotatable, flexible neck-model provides the basis for our analysis to evaluate the tissue shift and to invent the new navigation system for endoscopic neck surgery. The total registration error of the system was 2 mm.
Endovascular Seldinger Needle Placement: A Simulator for Examining Haptic Skills
Authors: Singapogu Ravikiran B.  , Kerr Charles M.  , Eidt John F.  , Pagano Christopher C.  , Burg Timothy C.  , Smith Dane E.  , Burg Karen J.L.
Published: February 2025

In this work, we develop an affordable haptic simulator for examining haptic skills required for endovascular Seldinger needle placement.
Interactive Planning of Cryotherapy Using Physics-Based Simulation
Authors: Talbot Hugo  , Lekkal Myriam  , Bessard-Duparc Remi  , Cotin Stephane
Published: February 2025

Cryotherapy is a rapidly growing minimally invasive technique for the treatment of certain tumors. It consists in destroying cancer cells by extreme cold delivered at the tip of a needle-like probe. As the resulting iceball is often smaller than the targeted tumor, a key to the success of cryotherapy is the planning of the position and orientation of the multiple probes required to treat a tumor, while avoiding any damage to the surrounding tissues. In order to provide such a planning tool, a number of challenges need to be addressed such as fast and accurate computation of the freezing process or interactive positioning of the virtual cryoprobes in the pre-operative image volume. To address these challenges, we present an approach which relies on an advanced computational framework, and a gesture-based planning system using contact-less technology to remain compatible with a use in a sterile environment.
Virtual Reality for Improving Body Image Disorders and Weight Loss after Gastric Band Surgery: A Case Series
Authors: Cárdenas-López Georgina  , Torres-Villalobos Gonzalo  , Martinez Perla  , Carreño Vanessa  , Duran Ximena  , Dakanalis Antonios  , Gaggioli Andrea  , Riva Giuseppe
Published: February 2025

Laparoscopic Adjustable Gastric Banding (LAGB) is a common surgery method used to help obese patients to lose weight. However, even if LAGB is able to produce a durable and relevant weight loss, it is less effective in improving body image: as demonstrated by a recent study, obese patients with a body image disorder in the pre-operative stage continue to show this even 13 months after the operation. In this presentation we will discuss the possible role of virtual reality (VR) in addressing this problem within an integrated cognitive behavioral approach. To test this approach, a case series of three LAGB patient who experienced body dissatisfaction even after a >30/40% excess body weight loss, is presented and discussed. At the end of the 6-week protocol the patients experienced a 15%–20% further reduction of their weight. This reduction was also matched by a general improvement of the psychological state. Both the weight loss and the level of well-being were further improved after a three-month follow-up.
Design and Validation of 3D Printed Complex Bone Models with Internal Anatomic Fidelity for Surgical Training and Rehearsal
Authors: Unger Bertram J.  , Kraut Jay  , Rhodes Charlotte  , Hochman Jordan
Published: February 2025

Physical models of complex bony structures can be used for surgical skills training. Current models focus on surface rendering but suffer from a lack of internal accuracy due to limitations in the manufacturing process. We describe a technique for generating internally accurate rapid-prototyped anatomical models with solid and hollow structures from clinical and microCT data using a 3D printer. In a face validation experiment, otolaryngology residents drilled a cadaveric bone and its corresponding printed model. The printed bone models were deemed highly realistic representations across all measured parameters and the educational value of the models was strongly appreciated.
An Immersive Surgery Training System With Live Streaming Capability
Authors: Yang Yang  , Guo Xinqing  , Yu Zhan  , Steiner Karl V.  , Barner Kenneth E.  , Bauer Thomas L.  , Yu Jingyi
Published: February 2025

Providing real-time, interactive immersive surgical training has been a key research area in telemedicine. Earlier approaches have mainly adopted videotaped training that can only show imagery from a fixed view point. Recent advances on commodity 3D imaging have enabled a new paradigm for immersive surgical training by acquiring nearly complete 3D reconstructions of actual surgical procedures. However, unlike 2D videotaping that can easily stream data in real-time, by far 3D imaging based solutions require pre-capturing and processing the data; surgical trainings using the data have to be conducted offline after the acquisition. In this paper, we present a new real-time immersive 3D surgical training system. Our solution builds upon the recent multi-Kinect based surgical training system [1] that can acquire and display high delity 3D surgical procedures using only a small number of Microsoft Kinect sensors. We build on top of the system a client-server model for real-time streaming. On the server front, we efficiently fuse multiple Kinect data acquired from different viewpoints and compress and then stream the data to the client. On the client front, we build an interactive space-time navigator to allow remote users (e.g., trainees) to witness the surgical procedure in real-time as if they were present in the room.
Do Not Forget the Oldest Old: Design Principles for the 80+
Authors: Chan Malcolm W.C.  , Truong Susan  , Cheung Jeffrey J.H.  , Whitehead Cynthia  , Dubrowski Adam
Published: February 2025

A significant amount of research has been conducted regarding the design of Internet applications for the elderly. Concomitantly, researchers have been applying online technologies to healthcare for older adults. The oldest old (for our purposes, defined as older adults aged 80+) are increasingly adopting the use of the Internet and likely have different needs than those who are between 55 and 80 years old. The main results from a literature review on the existing research in human factors and design for older adults is presented. These results highlight the need for more research in human factors and design in the much neglected population group, the oldest old.
Computer Assisted Treatment Prediction of Low Back Pain Pathologies
Authors: Gal Norbert  , Stoicu-Tivadar Vasile  , Andrei Diana  , Nemeş Dan Ion  , Nădăşan Emanuela
Published: February 2025

The paper presents a fuzzy inference system based prediction with the role to determine the appropriate action for patients that presents lower back pain. If not treated correctly lower back pain can degenerate in various diseases. The system infers three possible actions: (1) spinal cord surgery, (2) medication combined with exercises and (3) no action needed. The system takes in consideration the age and sex of the patient, a pain intensity parameter, the metabolic rate of the patient and mobility parameters from the Zebris Mobility device. In total 243 rules have been formulated but only 21% of the rules suggests surgery. The initial results are promising; there is a correlation of 0.83% between the control results and the results from the system.
Belgian Primary Care EPR: Assessment of Nationwide Routine Data Extraction
Authors: De Clercq Etienne  , van Casteren Viviane  , Bossuyt Nathalie  , Goderis Geert  , Moreels Sarah
Published: February 2025

Starting in 2009, the first ever Belgian nationwide data collection network using routine data extracted from primary care EPR (upload method) has been built from scratch. The network also uses a manual web-based data collection method. This paper compares these two methods by analysing missing and most recent values for certain parameters. We collected data from 4954 practices, pertaining to 29,180 patients. Mean values for the most recent parameters were similar regardless of which data collection method was used. Many missing recent values (>46%) were found for all of the parameters when using the upload method. It seems that, in Belgium, uploading routine data from primary care EPR on a large scale is suitable and allows the collection of chronological retrospective data. However, the method still requires major, carefully controlled improvements.
Connecting Cloud-Based Personal Health Records with an XDS Affinity Domain to Provide Additional Information at the Point-of-Care
Authors: Huber Patrick  , Mitsch Christoph  , Sabutsch Stefan  , Schmidt-Erfurth Ursula
Published: February 2025

Due to the increasing use of Electronic Health Records by healthcare providers and the trend towards the use of Personal Health Records by patients the potential need to integrate these two types of medical documentation emerged. The introduction of the ELGA (Elektronische Gesundheitsakte, EHR) during the next few years is reason enough to propose possibilities to directly involve the patient into the data acquisition process in form of generating personal health data (e.g. vital signs, etc.) at home. In particular patients with chronic diseases will benefit from this integrated architecture. Furthermore, patients could archive all documents for their own use and responsibility. This article reviews literature about integration possibilities for personal and electronic health records and proposes an architecture which integrates data from patient-side into an affinity domains' XDS document repository.
Framework for Near-Field-Communication-Based Geo-Localization and Personalization for Android-Based Smartphones—Application in Hospital Environments
Authors: Meng Philipp  , Fehre Karsten  , Rappelsberger Andrea  , Adlassnig Klaus-Peter
Published: February 2025

Various applications using near field communication (NFC) have been developed for the medical sector. As a method of short-range wireless contact-driven data transfer, NFC is a useful tool in medicine. It can be used to transfer data such as blood pressure, control adherence to medication, or transmit in vivo data. The first proposed general framework uses NFC as a mechanism for indoor geo-localization in hospitals. NFC geo-localization is economical compared to classical concepts using indoor GPS or WLAN triangulation, and the granularity of location retrieval can be defined at a tag level. Using this framework, we facilitate the development of medical applications that require exact indoor geo-localization. Multi-user Android systems are addressed in the second framework. Using private NFC tags, users are able to carry on their personal settings for enabled applications. This eliminates the need for multiple user accounts on common Android devices, improves usability, and eases technical administration. Based on the prototypes presented here, we show a novel concept of using NFC-enabled Android devices in hospital environments.
Too Many Attributes and Consumer's Dysfunction
Authors: Ebina Takeshi  , Kinjo Keita
Published: February 2025

This study analyzes consumer purchasing behavior by introducing voluminous product information into a consumer decision-making model. We focus on the case where consumers and firms have insufficient preferences for product attributes. This situation can apply to the case where a new product or product with new features is introduced into a market. We analyze consumer dysfunction in the presence of excessive alternatives and investigate how many products and product attributes are offered when selling a product. Following the ideal point model, we construct a new model and investigate it. Furthermore, by relaxing the assumptions made in the theoretical model, we numerically investigate and verify the robustness of our theoretical results. The results reveal that consumers may not be able to choose the best product because of confusion and dysfunction of their preferences for product attributes. This confusion causes consumers to choose each product with equal probability.
Improving of the weight normalization method on alternatives in AHP and ANP
Authors: Nishizawa Kazutomo
Published: February 2025

In this study, for the Analytic Hierarchy Process (AHP) and the Analytic Network Process (ANP), the improving normalization method is considered. In the traditional AHP and ANP, the sum of weights of alternatives is normalized to 1. Using this method, some problems, for example rank reversal, were pointed out. Based on the numerical results, one of the causes of these problems is the inappropriate normalizing process. Therefore, for the AHP and the ANP, at first, in this paper, two kind of normalization method are described. One is normalizing to 1 to the sum of the column vector of alternatives for each criterion, and other is normalizing to 1 to the maximum element of each column vector of alternatives. At second, some problems by using two kind of method are shown. At third, by applying proposed method to the verification example, it shows that the correct result is obtained. Finally, proposed normalization method is discussed and concluded.
Non-Topical Classification of Healthcare Information on the Web
Authors: Hirokawa Sachio  , Ishita Emi
Published: February 2025

The present paper collected the asthma related 4,762 Web pages from 1,759 sites using 6 queries. Each site is manually categorized by the standard topics of description and information dissemination, diary and idle talk and Q&A. By careful analysis, it turned out that the pages can be classified in non-topical categories such as “reading level”, “objectivity/subjectivity” and “reliability”. The manually assigned labels of non-topical categories are then used as learning data to apply SVM (support machine vector). The prediction performance (F-measure) were below 50% with the naive application of SVM. However, the prediction performance was improved over 50% by feature selection except for reading level.
A New Approach to the Vegetable Production and Distribution System
Authors: Ahrary Alireza  , Ludena R. Dennis A.
Published: February 2025

The multiple benefits of the Big Data new paradigm have being used in the novel nutrition-based vegetable production and distribution system in order to generate a healthy food recommendation to the end user, and to obtain different analytics results that could improve the system's efficiency. As next step in this study, the new paradigm Internet of Things (IoT) is included in the Big Data approach of the system to use its benefits, particularly automation and tracking technologies, to add much more data to the system to be processed in order to deliver to the user a much richer experience. In this regard, the IoT paradigm is bridging the real world with its virtual image, where devices located in different areas could exchange information each other without any type of supervision or control. But, spite of all the benefits that IoT could bring to society, the security of the information as well as privacy must be strongly enforced and managed in this new environment with unique characteristics. In our project we make a particular approach and security assessment of the use of IoT to provide automatic data to the system.
Farthest-Point Voronoi Region Sensitive Processing for Further Precise Maximum Query Results
Authors: Sato Hideki  , Narita Ryoichi
Published: February 2025

Regular Polygon based Search Algorithm (RPSA) was developed for approximately processing aggregate queries on remote spatial databases. However, Precision regarding maximum queries is required to be more precise under comparison with that regarding sum queries. To this end, RPSA is revised by making it sensitive to farthest-point Voronoi regions with regard to a set of query points. Experimental results on the revised RPSA using synthetic and real datasets show that Precision regarding maximum k-Nearest Neighbor (k-ANN) queries ranges between 0.98 and 1.00. Also, Precision regarding maximum range queries ranges between 0.95 and 1.00. From these results, the revised RPSA successfully improve Precision of maximum queries which becomes nearly equal to Precision of sum queries.
A Neural Network Model for Semi-supervised Sequential Multi-task Learning in Multi-label Pattern Recognition Problems
Authors: Higuchi Daisuke  , Ozawa Seiichi
Published: February 2025

In this paper, we propose an incremental neural network model for a general class of sequential multi-task classification problems where a training data of a task may not only have multiple class labels but also have task information. Such data property originates from the uncertainty of teaching signals given by a supervisor. To handle this type of classification problems, the proposed model consists of a three-layer feedforward neural network with long-term/short-term memories, and it has the following functions: one-pass incremental learning, task allocation, handling multi-label data, task consolidation, and knowledge transfer. We newly introduce the following two types of task consolidation functions other than the conventional error-based one: the task consolidation based on the co-occurrence relation of class labels and task information. In the experiments, we evaluate the proposed model for various kinds of data sets. The experimental results demonstrate that the proposed model has good performance in both classification and task categorization even if the task information is not always given.