bluuebunny/crossref_metadata_2025 huggingface dataset:
Biomedical Informatics and the Digital Component of the Exposome
Authors: Lopez-Campos Guillermo  , Merolli Mark  , Martin-Sanchez Fernando
Published: February 2025

Biomedical informatics plays a key role in the development of precision medicine and other new technology-enabled health disciplines. In this context, the exposome (defined as the whole set of exposures on an individual) has become a relevant topic. Although most of the research work in the exposome area has been conducted around the physical and chemical world, we sustain that in an increasingly digitised world more attention should be paid to the digital component of the exposome derived from the interactions of individuals with the digital world. We define this “Digital Exposome” as the whole set of tools and platforms that an individual use and the activities and processes that an individual engages with as part of his/her digital life. In addition we support that biomedical informatics can and should lead research in this area.
Case Report Form Reporter: A Key Component for the Integration of Electronic Medical Records and the Electronic Data Capture System
Authors: Matsumura Yasushi  , Hattori Atsushi  , Manabe Shiro  , Takahashi Daiyo  , Yamamoto Yuichiro  , Murata Taizo  , Nakagawa Akito  , Mihara Naoki  , Takeda Toshihiro
Published: February 2025

To improve the efficiency of clinical research, we developed a system to integrate electronic medical records (EMRs) and the electronic data capture system (EDC). EDC is divided into case report form (CRF) reporter and CDMS with CRF receiver with data communication using the operational data model (ODM). The CRF reporter is incorporated into the EMR to share data witth the EMR. In the data transcription type, doctors enter data using a progress note template, which are transmitted to the reporter template. It then generates the ODM. In the direct record type, reporter templates open from the progress note and generate narrative text to make record in the progress note. The configuration files for a study are delivered from the contents server to minimize the setup. This system has been used for 15 clinical studies including 3 clinical trials. This system can save labor and financial costs in clinical research.
Establishment of New National Rare Disease (Nambyo) Registry and Registry Guidelines in Japan
Authors: Mizushima Hiroshi  , Tanabe Mai  , Sugamori Yasutaka  , Sato Yoko  , Ogata Hiromitsu
Published: February 2025

A New legal structure for rare disease (nambyo) has been established in Japan this year, after 42 years of measures of nambyo. We have been accumulating registry for nambyo from 2003, however, as it was based on paper registration, quality was not enough.
Mining Adverse Events of Dietary Supplements from Product Labels by Topic Modeling
Authors: Wang Yefeng  , Gunashekar Divya R.  , Adam Terrence J.  , Zhang Rui
Published: February 2025

The adverse events of the dietary supplements should be subject to scrutiny due to their growing clinical application and consumption among U.S. adults. An effective method for mining and grouping the adverse events of the dietary supplements is to evaluate product labeling for the rapidly increasing number of new products available in the market. In this study, the adverse events information was extracted from the product labels stored in the Dietary Supplement Label Data-base (DSLD) and analyzed by topic modeling techniques, specifically Latent Dirichlet Allocation (LDA). Among the 50 topics generated by LDA, eight topics were manually evaluated, with topic relatedness ranging from 58.8% to 100% on the product level, and 57.1% to 100% on the ingredient level. Five out of these eight topics were coherent groupings of the dietary supplements based on their adverse events. The results demonstrated that LDA is able to group supplements with similar adverse events based on the dietary supplement labels. Such information can be potentially used by consumers to more safely use dietary supplements.
Chile's National Center for Health Information Systems: A Public-Private Partnership to Foster Health Care Information Interoperability
Authors: Capurro Daniel  , Echeverry Aisen  , Figueroa Rosa  , Guiñez Sergio  , Taramasco Carla  , Galindo César  , Avendaño Angélica  , García Alejandra  , Härtel Steffen
Published: February 2025

Despite the continuous technical advancements around health information standards, a critical component to their widespread adoption involves political agreement between a diverse set of stakeholders. Countries that have addressed this issue have used diverse strategies. In this vision paper we present the path that Chile is taking to establish a national program to implement health information standards and achieve interoperability. The Chilean government established an inter-agency program to define the current interoperability situation, existing gaps, barriers, and facilitators for interoperable health information systems. As an answer to the identified issues, the government decided to fund a consortium of Chilean universities to create the National Center for Health Information Systems. This consortium should encourage the interaction between all health care stakeholders, both public and private, to advance the selection of national standards and define certification procedures for software and human resources in health information technologies.
Towards a Usability and Error “Safety Net”: A Multi-Phased Multi-Method Approach to Ensuring System Usability and Safety
Authors: Kushniruk Andre  , Senathirajah Yalini  , Borycki Elizabeth
Published: February 2025

The usability and safety of health information systems have become major issues in the design and implementation of useful healthcare IT. In this paper we describe a multi-phased multi-method approach to integrating usability engineering methods into system testing to ensure both usability and safety of healthcare IT upon widespread deployment. The approach involves usability testing followed by clinical simulation (conducted in-situ) and “near-live” recording of user interactions with systems. At key stages in this process, usability problems are identified and rectified forming a usability and technology-induced error “safety net” that catches different types of usability and safety problems prior to releasing systems widely in healthcare settings.
Eliciting the Intension of Drug Value Sets – Principles and Quality Assurance Applications
Authors: Bahr Nathan J.  , Nelson Scott D.  , Winnenburg Rainer  , Bodenreider Olivier
Published: February 2025

Value sets (VSs) used in electronic clinical quality measures are lists of codes from standard terminologies (“extensional” VSs), whose purpose (“intension”) is not always explicitly stated. We elicited the intension for the 09/01/2014 release of extensional medication value sets by comparison to drug classes from the October 2014 release of RxClass. Value sets matched drug classes if they shared common ingredients, as evidenced by Jaccard similarity score. We elicited the intension of 80 extensional value sets. The average Jaccard similarity was 0.65 for single classes and 0.80 for combination classes, with 34% (27/80) of the value sets having high similarity scores. Manual review by a pharmacist indicated 51% (41/80) of the drug classes selected as the best mapping for a value set matched the intension reflected in that value set name. This approach has the potential for facilitating the development and maintenance of medication value sets.
Effects of Implementing a Tree Model of Diagnosis into a Bayesian Diagnostic Inference System
Authors: Iwai Satoshi  , Kawazoe Yoshimasa  , Imai Takeshi  , Ohe Kazuhiko
Published: February 2025

To estimate a diagnostic probability similarly to experts using answers to interviews, we developed a system that fundamentally behaves as a Bayesian model. For predefined interviews, we defined the sensitivity and specificity related to one or more diagnoses. Additionally, we used a predefined parent–child relation between diagnoses to decrease the number of parameters to set. After calculating the disease probability, we trained the model using the difference of post-test probability between computer calculations and three experts' opinions. We evaluated the effects of setting up tree structures. When using a tree structure, the model trained faster and produced better fitting results than the model without tree structure. Training with multiple raters' training data confused the model. The scores worsened in later epochs. Herein, we present the new method's benefits and characteristics.
Semantic Web Service Delivery in Healthcare Based on Functional and Non-Functional Properties
Authors: Schweitzer Marco  , Gorfer Thilo  , Hörbst Alexander
Published: February 2025

In the past decades, a lot of endeavor has been made on the trans-institutional exchange of healthcare data through electronic health records (EHR) in order to obtain a lifelong, shared accessible health record of a patient. Besides basic information exchange, there is a growing need for Information and Communication Technology (ICT) to support the use of the collected health data in an individual, case-specific workflow-based manner. This paper presents the results on how workflows can be used to process data from electronic health records, following a semantic web service approach that enables automatic discovery, composition and invocation of suitable web services. Based on this solution, the user (physician) can define its needs from a domain-specific perspective, whereas the ICT-system fulfills those needs with modular web services. By involving also non-functional properties for the service selection, this approach is even more suitable for the dynamic medical domain.
Leveraging Event Reporting Through Knowledge Support: A Knowledge-Based Approach to Promoting Patient Fall Prevention
Authors: Yao Bin  , Kang Hong  , Miao Qi  , Zhou Sicheng  , Liang Chen  , Gong Yang
Published: February 2025

Patient falls are a common safety event type that impairs the healthcare quality. Strategies including solution tools and reporting systems for preventing patient falls have been developed and implemented in the U.S. However, the current strategies do not include timely knowledge support, which is in great need in bridging the gap between reporting and learning. In this study, we constructed a knowledge base of fall events by combining expert-reviewed fall prevention solutions and then integrating them into a reporting system. The knowledge base enables timely and tailored knowledge support and thus will serve as a prevailing fall prevention tool. This effort holds promise in making knowledge acquisition and management a routine process for enhancing the reporting and understanding of patient safety events.
Design of a Mobile Application for Transfusion Medicine
Authors: Albornoz M.A.  , Márquez S.  , Rubin L.  , Luna D.
Published: February 2025

One of the most frequent error in transfusion medicine is the failure in verifying the patient's identity prior to transfusion. This paper describes the design and development of a Mobile Application (MA) for transfusion medicine. The app uses barcode and QR reading technology for the verification of the patient's identity and the administration of blood components when making a blood transfusion. Physicians, developers, technicians of transfusion medicine and a User Centered Design team participated in the design. The inclusion of end users was fundamental to get full representativeness of their workflow. The project was based on agile methodologies of project management and software development.
An Innovative Technology to Support Independent Living: The Smarter Safer Homes Platform
Authors: Karunanithi Mohanraj  , Zhang Qing
Published: February 2025

Australian population aged over 65 years is 14% (3.3 million) and this expected to increase to 21% by 2053 (8.3 million), of which 1.9% to 4.2% is attributed to Australians over 85 years. With increase in ageing, there is high prevalence in long-term health conditions and more likely multiple visits to the doctors or the hospitals, particularly when one's functional condition declines. This adds burden to the already stretched health system such as the overcrowding of emergency departments in hospitals. This is partly due to many ageing patients with high care needs occupying significant number of hospital beds because they are waiting for entry to the limited placements in residential care. To address this increase in ageing population and its impact in the society, the Australian government has funded aged care reforms for initiatives for older community stay at home longer. Recently, this was implemented through consumer directed age care reform. Advances in information and communication technologies, particularly in the advancement of lifestyle technologies and its increased use, show promise in the uptake of telehealth approach to support older people to live longer in their homes. In 2011, CSIRO took the initiative to a develop consumer designed innovative platform that would assist and support the older community in their functional ability and health for day to day living in their home environment. This platform was called the Smarter Safer Homes technology. The Smarter Safer Homes platform infers the Activities of Daily Living information from a passive sensor-enabled environment and correlates the information with home-based health monitoring measurements. The use of sensors enables the information to be captured in an unobtrusive manner. This information is then provided to the individual in the household through an iPad application while information can also be shared with formal and informal carers. The platform has undergone a few pilot studies to explore an objective and individualised approach to Activities of daily living based on an individual's profile and its applicability in multi-resident home setting in individual's in regional Queensland. Furthermore, the platform is being validated in a clinical study for its application in the aged care service in various geographical settings such as in urban and remote communities. This paper describes the platform, outcomes of pilot studies, and its future application.
Collect Once – Use Many Times: The Research Potential of Low Back Pain Patients' Municipal Electronic Healthcare Records
Authors: Toftdahl Anne Katrine Skjølstrup  , Pape-Haugaard Louise Bilenberg  , Palsson Thorvaldur Skuli  , Villumsen Morten
Published: February 2025

Collect Once – Use Many Times can possibly increase the research potential of clinical data from electronic healthcare records (EHR). The objective of this study was to achieve an increased understanding of the research potential of low back pain patients' municipal EHR by assessing the data quality. This explanatory sequentially mixed-methods case study consists of descriptive- and content analysis. The descriptive analysis was based on data extracted from the municipal EHR. The indicators chosen were pain and physical function. Included subjects were low back pain patients in the Northern Denmark. For the content analysis, clinical notes from the municipal EHR was used. The descriptive analysis (n=172) showed that the outcome measure for pain was documented in 50% of the municipal EHR and the outcome measure for physical function was documented in 48% of the municipal EHR. The content analysis (n=5) revealed imprecise, inconsistent, and nonsystematic use of outcome measures. In conclusion, the poor data quality observed is a potential barrier for introducing the Collect Once - Use Many Times paradigm, which is a prerequisite for reusing clinical data for quality assessment and research purposes.
3000PA—Towards a National Reference Corpus of German Clinical Language
Authors: Hahn Udo  , Matthies Franz  , Lohr Christina  , Löffler Markus
Published: February 2025

We introduce 3000PA, a clinical document corpus composed of 3,000 EPRs from three different clinical sites, which will serve as the backbone of a national reference language resource for German clinical NLP. We outline its design principles, results from a medication annotation campaign and the evaluation of a first medication information extraction prototype using a subset of 3000PA.
Gaining Insights on Nasopharyngeal Carcinoma Treatment Outcome Using Clinical Data Mining Techniques
Authors: Ghaibeh A. Ammar  , Kasem Asem  , Ng Xun Jin  , Nair Hema Latha Krishna  , Hirose Jun  , Thiruchelvam Vinesh
Published: February 2025

The analysis of Electronic Health Records (EHRs) is attracting a lot of research attention in the medical informatics domain. Hospitals and medical institutes started to use data mining techniques to gain new insights from the massive amounts of data that can be made available through EHRs. Researchers in the medical field have often used descriptive statistics and classical statistical methods to prove assumed medical hypotheses. However, discovering new insights from large amounts of data solely based on experts' observations is difficult. Using data mining techniques and visualizations, practitioners can find hidden knowledge, identify interesting patterns, or formulate new hypotheses to be further investigated. This paper describes a work in progress on using data mining methods to analyze clinical data of Nasopharyngeal Carcinoma (NPC) cancer patients. NPC is the fifth most common cancer among Malaysians, and the data analyzed in this study was collected from three states in Malaysia (Kuala Lumpur, Sabah and Sarawak), and is considered to be the largest up-to-date dataset of its kind. This research is addressing the issue of cancer recurrence after the completion of radiotherapy and chemotherapy treatment. We describe the procedure, problems, and insights gained during the process.
A Qualitative Evaluation of a Decision Support System for District-Level Disease Surveillance in Sierra Leone
Authors: Pore Meenal  , Arnold Anna-Lena  , Mugambi Purity  , Myers Ralph  , Sengeh David  , Sesay Tom  , Tran Anh-Minh
Published: February 2025

A decision support system for district-level disease surveillance was piloted with the Port Loko District Health Management Team in Sierra Leone. Through a qualitative evaluation, the study explores the impact of the system on disease surveillance workflows. Results indicate that the system aided decision making for operational tasks, and reduced the time taken to analyze and report surveillance data. In addition, the study discusses the challenges of deploying a pilot system during the Ebola recovery in Sierra Leone, and proposes a high-level architecture for a modular, interoperable decision support system for disease surveillance for public health decision makers in low-resource health systems.
Preliminary Evaluation of an Electronic Patient Prioritization Tool for Pediatric Emergency Department
Authors: Schiro Jessica  , Gauthier Pierre-François  , Dubos François  , Pelayo Sylvia  , Marcilly Romaric
Published: February 2025

The study presents the evaluation of the reliability of the information displayed on the user interface of a homegrown electronic patient prioritization tool dedicated to pediatric emergency department (namely Optimum). Two ergonomists shadowed physicians and nurses throughout their shift in order to (i) identify consistencies and discrepancies between the actual step of the patients in the care process and their assigned step in Optimum and (ii) to understand the causes of the discrepancies. Even if some discrepancies are noted, results show that Optimum provides a quite good reflection of the actual position of the patients in the care process. The use of ethnographic methods allows to understand the cause of the discrepancies.
From Narratives to Numbers: Data Work and Patient-Generated Health Data in Consultations
Authors: Lindroth Tomas  , Islind Anna Sigridur  , Steineck Gunnar  , Lundin Johan
Published: February 2025

This article presents preliminary findings on how the introduction of patient-generated health data (PGHD) triggers changes during patient-nurse consultations. This article builds on a two-year case study, examining the work practice at a cancer rehabilitation clinic at a Swedish Hospital using PGHD. The study focuses on how nurses' use data, gathered by patients with a mobile phone app, during consultations. The use of PGHD introduce a change in the translation work, the work of turning rich patient descriptions and transform them into data, during the consultation for documentation and clinical decision-making. This change affects precision, questions asked and the use of visualizations as well as the patient-nurse decision making.
A Knowledge-Base for a Personalized Infectious Disease Risk Prediction System
Authors: Vinarti Retno  , Hederman Lucy
Published: February 2025

We present a knowledge-base to represent collated infectious disease risk (IDR) knowledge. The knowledge is about personal and contextual risk of contracting an infectious disease obtained from declarative sources (e.g. Atlas of Human Infectious Diseases). Automated prediction requires encoding this knowledge in a form that can produce risk probabilities (e.g. Bayesian Network – BN). The knowledge-base presented in this paper feeds an algorithm that can auto-generate the BN. The knowledge from 234 infectious diseases was compiled. From this compilation, we designed an ontology and five rule types for modelling IDR knowledge in general. The evaluation aims to assess whether the knowledge-base structure, and its application to three disease-country contexts, meets the needs of personalized IDR prediction system. From the evaluation results, the knowledge-base conforms to the system's purpose: personalization of infectious disease risk.
Strategies for Effectively Documenting Sexual Orientation and Gender Identity in Electronic Health Record
Authors: Frangella Julia  , Otero Carlos  , Luna Daniel
Published: February 2025

In this communication we identify strategies for effectively documenting Sexual Orientation and Gender Identity in Electronic Health Records. For this review a multidisciplinary group composed by three physicians, a nurse, an engineer and a lawyer analyzed the evidence in bibliography related to the topic and summarized the results. After analyzing the information, we summarized and classified them into three major topics: To request, to store and to display and access to the information. How to standardize those data and where data specifically will be populated in EHRs have not been answered yet. The target of all of these efforts should be: to be sensitive with the needs of the patient and to ensure high quality of care.
An Automated Technique to Construct a Knowledge Base of Traditional Chinese Herbal Medicine for Cancers: An Exploratory Study for Breast Cancer
Authors: Nguyen Phung Anh  , Yang Hsuan-Chia  , Xu Rong  , Li Yu-Chuan (Jack)
Published: February 2025

Traditional Chinese Medicine utilization has rapidly increased worldwide. However, there is limited database provides the information of TCM herbs and diseases. The study aims to identify and evaluate the meaningful associations between TCM herbs and breast cancer by using the association rule mining (ARM) techniques. We employed the ARM techniques for 19.9 million TCM prescriptions by using Taiwan National Health Insurance claim database from 1999 to 2013. 364 TCM herbs-breast cancer associations were derived from those prescriptions and were then filtered by their support of 20. Resulting of 296 associations were evaluated by comparing to a gold-standard that was curated information from Chinese-Wikipedia with the following terms, cancer, tumor, malignant. All 14 TCM herbs-breast cancer associations with their confidence of 1% were valid when compared to gold-standard. For other confidences, the statistical results showed consistently with high precisions. We thus succeed to identify the TCM herbs-breast cancer associations with useful techniques.
Asynchronous Dermatology Teleconsultations Using a Personal Health Record
Authors: Plazzotta Fernando  , Sommer Janine Arlette  , Marquez Fosser Santiago Nicolás  , Luna Daniel Roberto
Published: February 2025

Health information and communication technologies such as telemedicine provide alternatives for patient and physician communication. An increasing number of patients, providers and institutions are using this technologies to seek or provide health care. Asynchronous consultations requires a service of storing and forwarding health related information by the patient to the specialist physician or other healthcare provider. Dermatology is one of the major medical specialties in which telemedicine as proven benefits. There are many described deployments of asynchronous teleconsultation for dermatology, but in most cases telemedicine applications work as stand alone solutions. The present work describes the design and deployment of an asynchronous dermatological teleconsultation service which uses the interaction of the Electronic Health Record and the Personal Health Record in a high complexity university hospital.
openEHR Based Systems and the General Data Protection Regulation (GDPR)
Authors: Sousa Mariana  , Ferreira Duarte  , Santos-Pereira Cátia  , Bacelar Gustavo  , Frade Samuel  , Pestana Olívia  , Cruz-Correia Ricardo
Published: February 2025

The concerns about privacy and personal data protection resulted in reforms of the existing legislation in European Union (EU). The General Data Protection Regulation (GDPR) aims to reform the existing measures on the topic of personal data protection of the European Union citizens, with a strong input on the rights and freedoms of people and in the establishment of rules for the processing of personal data. OpenEHR is a standard that embodies many principles of interoperable and secure software for electronic health records. This work aims to understand to what extent the openEHR standard can be considered a solution for the requirements needed by GDPR. A list of requirements for a Hospital Information Systems (HIS) compliant with GDPR and an identification of openEHR specifications was made. The requirements were categorized and compared with the specifications. The requirements identified for the systems were matched with the openEHR specifications, which result in 16 requirements matched with openEHR. All the specifications identified matched at least one requirement. OpenEHR is a solution for the development of HIS that reinforce privacy and personal data protection, ensuring that they are contemplated in the system development. The institutions can secure that their Eletronic Health Record are compliant with GDPR while safeguarding the medical data quality and, as a result, the healthcare delivery.
Mapping of Health Care Providers for People with Rare Diseases – From Vision to Implementation
Authors: Schaefer Johanna  , Tegtbauer Niels  , Pfeiffer Wulf  , Wagner Thomas O.F.  , Storf Holger
Published: February 2025

se-atlas – the health service information platform for rare diseases – is part of the German National Action Plan for People with Rare Diseases. The website www.se-atlas.de provides an overview of health care providers and support groups focusing on rare diseases in Germany. Since the start of se-atlas in 2013, several strategies are being developed and evaluated. This paper gives an overview about the expectations and visions for se-atlas at the beginning of the project, the challenges and lessons learned within the project period and how se-atlas is implemented today.
Development of a Clinical Decision Support System in Intensive Care
Authors: Pflanzl-Knizacek Lucas  , Bergmoser Katharina  , Mattersdorfer Karin  , Schilcher Gernot  , Baumgartner Christian
Published: February 2025

Background: Intensive care is confronted with an increasing complexity and large amounts of data provided by new technological tools. One way of assisting health care professionals is providing effective clinical decision support (CDS) systems.
A New Machine Learning Framework for Understanding the Link Between Cannabis Use and First-Episode Psychosis
Authors: Alghamdi Wajdi  , Stamate Daniel  , Stahl Daniel  , Zamyatin Alexander  , Murray Robin  , Di Forti Marta
Published: February 2025

Lately, several studies started to investigate the existence of links between cannabis use and psychotic disorders. This work proposes a refined Machine Learning framework for understanding the links between cannabis use and 1st episode psychosis. The novel framework concerns extracting predictive patterns from clinical data using optimised and post-processed models based on Gaussian Processes, Support Vector Machines, and Neural Networks algorithms. The cannabis use attributes' predictive power is investigated, and we demonstrate statistically and with ROC analysis that their presence in the dataset enhances the prediction performance of the models with respect to models built on data without these specific attributes.
Design and Implementation of Big Data-Based Documents to Optimize Medical Coding
Authors: Noussa-Yao Joseph  , Heudes Didier  , Degoulet Patrice
Published: February 2025

Clinical information systems (CISs) in some hospitals streamline the data management from data warehouses. These warehouses contain heterogeneous information from all medical specialties that offer patient care services. It is increasingly difficult to manage large volumes of data in a specific clinical context such as quality coding of medical services. The document-based Not Only SQL (NO-SQL) model can provide an accessible, extensive and robust coding data management framework while maintaining certain flexibility. This paper focus on the design and implementation of a big data-coding warehouse, it also defines the rules to convert a conceptual model of coding into a document-oriented logical model. Using that model, we implemented, analyzed a big data-coding warehouse via the Mongodb database, and evaluated it using data research mono- and multi-criteria and then calculated the precision of our model.
Implementation of Ship Energy Efficiency Requirements in Offshore Shipping Industry
Authors: Belev Blagovest  , Stoyanov Rumen  , Hanzu-Pazara Radu
Published: February 2025

The International Maritime Organization (IMO), through its Maritime Environmental Protection Committee (MEPC), has been carrying out substantial work to provide the fundamental conditions for the reduction of greenhouse gas emissions from international shipping since 1997, following the adoption of the Kyoto Protocol and the 1997 MARPOL Conference. Many documents, issued in this respect, are dedicated to different types of vessels. More of the requirements and regulations for establishing of efficiency criteria are based on commercial activities of the vessels and respective fuel consumption. There is the big difference between offshore vessels and all other vessels. Offshore shipping industry has another criteria for effective fuel consumption. As longest as the job is with very high risk Safety is with high priority. The offshore industry try to find another way and means for implementation of MARPOL Annex VI requirements. The article summarizes Classification Societies requirements regarding offshore vessels. The requirements are compare with IMO Resolutions in this field and conclusions are made. The authors has made proposals to education system which are related to STCW Convention Code, Part B.
Heavy-Lifting: Coupled Stability & Structural Analysis in a Load-Out Operation
Authors: Dardel Stéphane  , Danese Nick  , Morbelli Jean-Luc  , Flouret Sylvain
Published: February 2025

The economic and technical challenges of large-scale load-in/out operations require the assurance provided by specialized and integrated engineering software that provides leading-edge support to preparation and planning and helps ensure enhanced safety and quality control. This case-study describes the planning of a load-in operation by a Self-Propelled Modular Transporter (SPMT), for which all technical and environmental constraints are integrated in a quasi-dynamic model, developed in a combined GHS™ (hydrostatics & stability) and MAESTRO Marine™ (ship-specialized FE) environment. Model and calculations address and cater to tide, wind, mooring forces (winches, anchors, etc.), ballast, pump capacity, verification at each stage of the loading of draft and trim, stability, hull girder bending moment and deflection, compliance with operational limits and Regulations, etc. The realistic Finite Element structural and the stability models are loaded in synchrony (hydrostatics and SPMT). The integrated GHS and MAESTRO environment allows tracking and managing the combined hydro and mass loading effects in quasi-dynamic mode: the hydrostatically balanced, MAESTRO receives tank loads from GHS, and runs detailed stress analysis and limit state evaluation of the structure, thereby ascertaining the structural integrity and girder deformation patterns of the carrier.
Hybrid Energy and Propulsion System for Vessels in Timetable Operation
Authors: Einsiedler Martin
Published: February 2025

The energy consumption of propulsion and all on board systems is becoming more and more into the focus of attention in shipbuilding and operation. After some ample and intensive analysis and measurements of multiple operational profiles of ships, it was determined that a new, hybrid propulsion system, will be the optimal solution to reduce fuel consumption in timetable operation. This parallel hybrid system, which incorporates propulsion as well as the general energy management of all energy consuming parts on board as a holistic system, so that the distinct, transient processes can be smoothed out as much as possible. This allows the multiple diesel engines, which are the main energy producers, to work at their most efficient operating point (or they shut off entirely due to battery buffers). The focus of the project is set on considering the integration of the different systems, their optimal cooperation with each other and the required system dynamics. First measurements at the pilot vessel show that fuel consumption can be reduced by up to 25%. In addition, they show that, with the additional help of downsizing relevant components, the costs of operation can be reduced up to 40% (excl. crew costs).
A Ballast Allocation Technique to Minimize Fuel Consumption
Authors: Braidotti Luca  , Mauro Francesco  , Sebastiani Luca  , Bisiani Sergio  , Bucci Vittorio
Published: February 2025

Nowadays, fuel consumption reduction is a primary concern in order to minimize operative costs and emissions during navigation. On this purpose, ballast management play an important role, in order to find the best configuration for ship navigation. An optimal ballast water distribution ensures to find a floating position having the minimum fuel consumption while assuring the fulfillment of rules requirements related to strength and stability. Since ships are operating also in adverse sea state condition, optimal ballast conditions should be found also for service conditions, considering the impact of added resistance due to waves on the propeller and consequently to fuel consumption. Within an emergency decision support system, an optimum ballast system has been developed satisfying the above mentioned requirements. In order to assess the optimal ballast allocation in a fast and accurate way, the equations are linearized and solved by means of pseudo inverse matrix. The target of this process is to find for a defined set of ballast tanks the level, or rather the volume, of water to reach the optimum floating position. The procedure has been tested on a reference ship and the results are here reported and described.
Design of A Mobile APP for Empty Nest Elderly Patients with T2DM
Authors: Lv Xiaoyan  , Xia Jinghua  , Fu Lingling  , Cao Yingjuan
Published: February 2025

China has the largest number of diabetics in the world and there is ineffective glycemic control among empty nest elderly. A multidisciplinary team were made up and patient interviews were performed for the designation of APP which was intended to conduct disease guidance and condition monitoring for empty nest elderly with type 2 diabetes to improve self-management and outcomes. The draft version was accomplished.
The Design of Elderly Fracture Rehabilitation Software Based on “Information-Motivation-Behavioral Skills Model”
Authors: Wu Qiong  , Jiang Zhixia  , Su Tao  , Dai Yongya  , Huang Di  , Lai Rongfei  , Zhang Jingjing  , Song Lingxia
Published: February 2025

Guided by the information-motivation-behavioral skills IMB) model theoryan application software with the man-machine interactive unity is designed for meeting the elderly fracture patients' rehabilitation. The software is based on the present situation and rehabilitation needs of elderly patients with fracture rehabilitation training. It provides professional guidance and rehabilitation intervention, influences the rehabilitation behavior of elderly fracture patients from information and motivation factors, and promotes the quality of the implementation of active rehabilitation.
The Actual Use of an Electronic Medical Record (EMR) by Acute Care Nurses: Examining a Multidimensional Measure at Different Adoption Stages
Authors: Maillet Éric  , Sicotte Claude  , Mathieu Luc
Published: February 2025

An EMR should support the informational needs of nursing practice. However, a multidimensional measure of the actual use of an EMR in hospitals ranked at different adoption stages revealed significant results that should be addressed to enable nurses to bring their full contribution to their patients and to the healthcare team.
The Nursing Value Model: A Structured Approach to Measuring Nursing Care
Authors: Garcia Amy L.  , Jenkins Peggy
Published: February 2025

Value is defined as outcomes/cost of care [1]. Although nurses contribute significantly within the interdisciplinary care team, we struggle to measure the value of nursing care or the added value of each nurse caring for a patient. This presentation reveals findings of the Nursing Value Workgroup (Workgroup), a multi-year component of the Big Data and Nursing Knowledge Initiative [2]. Panelists will discuss: Construction of a common model to provide a basis for developing nursing business intelligence and analytics; development and publication of definitions and metrics for nursing value; creation of user stories to measure nurse sensitive phenomena; and establishment of a data warehouse to facilitate research. Initial findings from a multi-hospital study on pain management and value of care will be presented.
Video Review System for Sharing Tacit Knowledge of Clinical Nursing Practice
Authors: Majima Yukie  , Maekawa Yasuko  , Hirano Kayoko  , Inotani Takami  , Izumi Takako  , Shimada Satoshi  , Ishigame Atsushi
Published: February 2025

Nursing practice conducted in a clinical setting remains within the facility, giving no opportunities to be shared widely. This study was conducted to record practical knowledge of clinical nursing, to build a video database for nursing skills education to share that knowledge, and to assess the systematic operation of such a database. We conducted pilot practice for simplified creation of teaching material contents and for evaluation of the Saei system operation. Saei means “to scrutinize self-made videos”. In Saei, as regular submissions for academic journals, we presupposed that nursing skill videos of one's own creation would be submitted to make them available to others. We assumed that the skill videos to be submitted are “mainly video manuals for nursing or medical care skills, recognized their safety and reliability, and shot to be a reference for clinical nursing, nursing skills training and nursing education using methods to satisfy ethically considered Nursing Art”. This report describes relevant results.
Information Completeness and Consistency of Inpatient Fall-Event Reports
Authors: Kim Jihye  , Cho Insook  , Yoo Ahra  , Chae Jisun  , Jung Miran
Published: February 2025

Reporting system need to correctly classify information about adverse clinical management events to develop preventative and corrective strategies. We investigated the completeness and consistency of the data, collected using the fall-event reporting system of a hospital, to understand the strengths and weaknesses of the current system.
The Study of Nursing NAVI
Authors: Iwao Y.  , Tsuru S.  , Omori M.  , Inoue M.
Published: February 2025

We have examined the nurses' thinking process in their professional judgment and action in the Partogram of 170 labors by 17 Midwifery students in 2 years.
Using Innovation-Decision Model to Describe the Adoption to Utilization of HIV-Data for Decision-Making in LMICs
Authors: Gesicho Milka B.  , Babic Ankica
Published: February 2025

Data informed decision-making (DIDM) plays a fundamental role in the fight against HIV and AIDS in Low-and-Middle-Income Countries (LMICs). Despite the scale-up of HIV care services, supported by health information systems (HIS), cases of under-utilization of data in decision-making are still being reported at different levels of the health system. Literature revealing the process involved in data users' decision to adopt DIDM in LMICs is meager. To fill this gap, we employ the innovation-decision model to describe the stages of adoption of DIDM by data users. Thus, we extract reports on efforts to promote DIDM in HIV from existing literature, and map this to the model. We then identify important stages, which require emphasis in the adoption process. Hence, implementers could benefit from use of the innovation-decision model in understanding adoption process of DIDM.
Risk Thresholds and Risk Classifications Pose Problems for Person-Centred Care
Authors: Kaltoft Mette Kjer  , Nielsen Jesper Bo  , Dowie Jack
Published: February 2025

Classification of a continuous risk score into risk levels is common. However, while the absolute risk score is essential, it is arguably unethical to label anyone at ‘high, moderate or low risk’ of a serious event, simply because management based on a single criterion (e.g. avoiding the target condition) has been determined to be effective or cost-effective at a population level. Legally, mono-criterial risk labeling can inhibit the obtaining of a fully-informed, preference-based consent, since multiple considerations (various benefits and harms) matter to most individuals, not only the single criterion that is the basis of the provided risk category. These ethical and legal challenges can be met by preference-sensitive multi-criteria decision support tools. In this future vision paper, we demonstrate, at a conceptual proof-of-method level, how such decision support can and should be developed without reference to risk-level classifications. The statin decision is used as illustration, without any empirical claims.
Machine Learning to Identify Behavioral Determinants of Oral Health in Inner City Older Hispanic Adults
Authors: Yoon Sunmoo  , Choi Thomas  , Odlum Michelle  , Mitchell Dennis A.  , Kronish Ian M.  , Davidson Karina W.  , Finkelstein Joseph
Published: February 2025

We applied machine learning techniques to a community-based behavioral dataset to build prediction models to gain insights about minority dental health and population aging as the foundation for future interventions for urban Hispanics. Our application of machine learning techniques identified emotional and systemic factors such as chronic stress and health literacy as the strongest predictors of self-reported dental health among hundreds of possible variables. Application of machine learning algorithms was useful to build prediction models to gain insights about dental health and minority population aging.
An Online Differential Cost Estimator Tool to Support Cost Planning of Demographic and Health Surveys Using Mobile Electronic Device or Paper and Pen Methods: A Function of Sample Size
Authors: Zeleke Atinkut  , Naziyok Tolga  , Wilken Marc  , Röhrig Rainer
Published: February 2025

The use of mobile devices for a house to house interview-administered survey data collection is becoming a practice along with the paper-based data collection tools. Though the electronic data capture mechanism is supposed to improve the efficiency of the data collection mechanism and the quality of the data, there is limited evidence on the cost-effectiveness of the technologies. This project aims to develop an online pre-implementation survey cost estimator to support the planning and decision of implementing agency. Scalable costs with sample size were estimated using parametric cost estimating technique. In this article, we used Introduction, State of the art, Concept, Implementation, Lessons Learned (ISCIL) format to present the overall development process of this online cost estimator.
Interactive Feedback of Data Quality in Clinical Research. A Case Study from an Infectious Diseases Cohort
Authors: Glöckner Stephan  , Schindler Daniela  , Karch André
Published: February 2025

To improve data quality, clinical cohort studies require ongoing centralized data monitoring. Results of data quality monitoring are often reported in a general format, without individual feedback for different types of users within the research consortium. Several R packages provide the possibility for an easy to use approach to analyze and communicate information in interactive web-based forms. This article describes a pilot, which is applied in a German infectious disease cohort using interactive feedback and gamification to report data quality, to ultimately increase the quality of research outcomes.
Modeling Malware Prediction Using Artificial Neural Network
Authors: Anuar Syahid  , Ahmad Noor Azurati  , Sahibuddin Shamsul  , Ariffin Aswami  , Saupi Afifah  , Zamani Nazri Ahmad  , Jeffry Yasmin  , Efendy Firham
Published: February 2025

Malware attack is becoming one of the most threats to internet security. Botnet in specific, used to generate spam, carry out DDOS attacks, steal sensitive information becoming major threats for committing cybercrimes. In this paper, we propose an artificial neural network model to predict types of botnet for the next day attack. In this experiment, several number of hidden neurons are manipulated in order to minimize error. Moreover, in order to minimize the processing time, the model is running on graphical processing unit (GPU) and the performance is compared to computational processing unit (CPU). The experimental results indicate that the model produce lowest error on 500 number of hidden neurons and there are significant different between the running time between GPU and CPU.
The “Games of Argumentation” Web Platform
Authors: Baroni Pietro  , Borsato Serena  , Rago Antonio  , Toni Francesca
Published: February 2025

This demo presents the web system “Games of Argumentation”, which allows users to build argumentation graphs and examine them in a game-theoretical manner using up to three different evaluation techniques. The concurrent evaluations of arguments using different techniques, which may be qualitative or quantitative, provides a significant aid to users in both understanding game-theoretical argumentation semantics and pinpointing their differences from alternative semantics, traditional or otherwise, to differentiate between them.
Characterising Routine Physical Activity in the Office
Authors: Van Kasteren Yasmin  , Perimal-Lewis Lua  , Maeder Anthony
Published: February 2025

Workplace health is of concern to management and employees alike. Managers are concerned about the impact of health and wellbeing on productivity, while employees are concerned about impacts on quality of life. In the past two decades, there has been growing concern about the impact of sedentary behaviour at work. Before any interventions can be made to encourage physical activity at work proactively, it is desirable to understand the baseline characteristics of office based physical activity at work. Consumer wearable technology has provided a new and convenient mechanism for using personal monitoring to achieve remote observation of lifestyle related health behaviours. This paper describes how this technology can potentially be used to characterize different levels of workplace physical activity.