bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring Control in Health Information Systems Implementation
Authors: Ali Maryam  , Cornford Tony  , Klecun Ela
Published: February 2025

Health information systems promise opportunities for improved healthcare. However, these opportunities may become challenges and obstacles to practice. This research reflects on the outcomes of implementing healthcare information systems in three English hospitals. In each case qualitative methods were used to observe and interview doctors, nurses and pharmacists as they carried out their daily healthcare routines. The changes that the implementation of health information systems brought for both the clinical encounter, as well as health care professionals' work flow, were explored. We argue that such technologies have become a central orchestrator of the clinical setting, to the extent that they often impose control on healthcare practices. Using a socio-technical approach we seek to understand how information systems technology and healthcare professionals can work together rather than apart, or around one another.
Toward a Human-Centered Voluntary Medical Incident Reporting System
Authors: Gong Yang
Published: February 2025

Voluntary medical incident reports are a valuable source for studying adverse events and near misses. Underreporting and low quality of reports in local organizations, however, have become the impediments in identifying trends and patterns relating at the local, regional and national level. Human factors on usefulness and ease of use have shown their important role in acceptance of voluntary reporting systems. To understand and identify the obstacles of quality reporting, we employed a set of human-centered analysis methods to examine one-year voluntary medical incident reports of a University Hospital. We found about 30% of the reports labeled as “miscellaneous” and “other”, and their real incident types or error descriptions were identified through an in-depth recoding. Human-centered analyses show that the pre-defined reporting categories could serve well for the voluntary reporting need if reporters' tasks were better represented on user-friendly interfaces. We suggest that a human-centered, ontology based system design for voluntary reporting is feasible which could help improve completeness, accuracy, and interoperability among national and international standards.
Using a Business Rule Management System to Improve Disposition of Traumatized Patients
Authors: Neuhaus Philipp  , Noack Oliver  , Majchrzak Tim  , Ückert Frank
Published: February 2025

We propose a business rule management system that is used to optimize the dispatchment on a mass casualty incident. Using geospatial information from available ambulances and rescue helicopters, a business rule engine calculates an optimized transportation plan for injured persons. It automatically considers special needs like ambulances equipped for baby transportation or special decontamination equipment, e.g. to deal with an accident in a chemical factory. The rules used in the system are not hardcoded; thus, it is possible to redefine them on the fly without changing the program's source code. It is possible to load and save a rule set in case of a catastrophe. Furthermore, it is possible to automatically recalculate an already planned operation if it becomes clear that the rescue vehicles assigned are needed by a person with life-threatening injuries.
Identifying Best Practices for Clinical Decision Support and Knowledge Management in the Field
Authors: Ash Joan S.  , Sittig Dean F.  , Dykstra Richard  , Wright Adam  , McMullen Carmit  , Richardson Joshua  , Middleton Blackford
Published: February 2025

To investigate best practices for implementing and managing clinical decision support (CDS) in community hospitals and ambulatory settings, we carried out a series of ethnographic studies to gather information from nine diverse organizations. Using the Rapid Assessment Process methodology, we conducted surveys, interviews, and observations over a period of two years in eight different geographic regions of the U.S.A. We first utilized a template organizing method for an expedited analysis of the data, followed by a deeper and more time consuming interpretive approach. We identified five major categories of best practices that require careful consideration while carrying out the planning, implementation, and knowledge management processes related to CDS. As more health care organizations implement clinical systems such as computerized provider order entry with CDS, descriptions of lessons learned by CDS pioneers can provide valuable guidance so that CDS can have optimal impact on health care quality.
Design of a continuous multifaceted guideline-implementation strategy based on computerized decision support
Authors: van Engen-Verheul Mariëtte  , de Keizer Nicolette  , Hellemans Irene  , Kraaijenhagen Roderik  , Hasman Arie  , Peek Niels
Published: February 2025

Implementation of clinical practice guidelines into daily care is hindered by a variety of barriers related to professional knowledge, collaboration in teams and organizations, and practicability of the guidelines. Clinical computerized decision support (CCDS) has been shown to be one of the most effective instruments to improve compliance to practice guidelines by tackling barriers related to professional knowledge. To address other barriers, however, additional interventions are needed. In this study, a continuous multifaceted guidelineimplementation strategy was developed which is based on CCDS but extends beyond the professional knowledge barrier. Two additional interventions were designed and embedded with CCDS in a continuous quality improvement framework. First, to address barriers within teams and organizations guideline compliance data are periodically aggregated into feedback reports for care providers. Second, barriers related to practicability of the underlying guidelines are addressed in a guideline-maintenance cycle. A case study in the field of cardiac rehabilitation is presented to demonstrate the feasibility of the developed strategy.
TADAA: Towards Automated Detection of Anaesthetic Activity
Authors: Houliston Bryan  , Parry Dave  , Merry Alan
Published: February 2025

Task analysis is a valuable research method for better understanding the activity of anaesthetists in the operating room (OR), providing evidence for designing and evaluating improvements to systems and processes. It may also assist in identifying potential error paths to adverse events, ultimately improving patient safety. Human observers are the current ‘gold standard’ for capturing task data, but they are expensive and have cognitive limitations. Our current research – Towards Automated Detection of Anaesthetic Activity (TADAA) - aims to produce an automated task analysis system, employing Radio Frequency Identification (RFID) technology to capture anaesthetists' location, orientation and stance (LOS), and machine learning techniques to translate that data into low-level and high-level activity labels. In this paper we present details of the system design and promising results from LOS sensing testing in laboratory and highfidelity OR simulator settings.
Taking the Final Step to a Full Dichotomy of the Possible Winner Problem in Pure Scoring Rules
Authors: Baumeister Dorothea  , Rothe Jörg
Published: February 2025

The POSSIBLE WINNER problem asks, given an election where the voters' preferences over the candidates are specified only partially, whether a designated candidate can be made win. Betzler and Dorn [1] proved a result that is only one step away from a full dichotomy of this problem for the important class of pure scoring rules in the case of unweighted voters and an unbounded number of candidates: POSSIBLE WINNER is NP-complete for all pure scoring rules except plurality, veto, and the scoring rule with vector (2,1,…,1,0), but is solvable in polynomial time for plurality and veto. We take the final step to a full dichotomy by showing that POSSIBLE WINNER is NP-complete also for the scoring rule with vector (2,1,…,1,0).
Advances in Class Noise Detection
Authors: Sluban Borut  , Gamberger Dragan  , Lavra Nada
Published: February 2025

Noise filtering is usually used in data preprocessing to improve the accuracy of induced classifiers. Our goal is different: we aim at detecting noisy instances to be inspected by the domain expert in the phase of data understanding. Consequently, our noise detection algorithms should have high precision of class noise detection, where the precision-recall trade-off is modeled using the F-measure. New variants of class noise detection algorithms have been developed, including the high agreement random forest filter which ensures very high precision of identified erroneous data instances.
GNUsmail: Open Framework for On-line Email Classification
Authors: Carmona-Cejudo José M.  , Baena-García Manuel  , del Campo-Ávila José  , Morales-Bueno Rafael  , Bifet Albert
Published: February 2025

Real-time classification of massive email data is a challenging task that presents its own particular difficulties. Since email data presents an important temporal component, several problems arise: emails arrive continuously, and the criteria used to classify those emails can change, so the learning algorithms have to be able to deal with concept drift. Our problem is more general than spam detection, which has received much more attention in the literature.
Kernel Methods for Revealed Preference Analysis
Authors: Lahaie Sébastien
Published: February 2025

In classical revealed preference analysis we are given a sequence of linear prices (i.e., additive over goods) and an agent's demand at each of the prices. The problem is to determine whether the observed demands are consistent with utility-maximizing behavior, and if so, recover a representation of the agent's utility function. In this work, we consider a setting where an agent responds to non-linear prices and also allow for incomplete price information over the consumption set. We develop two different kernel methods to fit linear and concave utilities to such observations. The methods allow one to incorporate prior information about the utility function into the estimation procedure, and represent semi-parametric alternatives to the classical non-parametric approach. An empirical evaluation exhibits the relative merits of the two methods in terms of generalization ability, solution sparsity, and runtime performance.
Tableau-based Forgetting in 𝒜ℒ𝒞 Ontologies
Authors: Wang Zhe  , Wang Kewen  , Topor Rodney  , Zhang Xiaowang
Published: February 2025

In this paper, we propose two new approaches to forgetting for 𝒜ℒ𝒞 based on the well-known tableau algorithm. The first approach computes the result of forgetting by rolling up tableaux, and also provides a decision algorithm for the existence of forgetting in 𝒜ℒ𝒞. When the result of forgetting does not exist, we provide an incremental method for computing approximations of forgetting. This second approach uses variable substitution to refine approximations of forgetting and eventually obtain the result of forgetting. This approach is capable of preserving structural information of the original ontologies enabling readability and comparison. As both approaches are based on the tableau algorithm, their implementations can make use of the mechanisms and optimization techniques of existing description logic reasoners.
Recommendations Over Domain Specific User Graphs
Authors: Nakatsuji Makoto  , Fujiwara Yasuhiro  , Tanaka Akimichi  , Uchiyama Tadasu  , Ishida Toru
Published: February 2025

Content providers want to make recommendations across multiple interrelated domains such as music and movies. However, existing collaborative filtering methods fail to accurately identify items that may be interesting to the user but that lie in domains that the user has not accessed before. This is mainly because of the paucity of user transactions across multiple item domains. Our method is based on the observation that users who share similar items or who share social connections, can provide recommendation chains (sequences of transitively associated edges) to items in other domains. It first builds domain-specific-usergraphs (DSUGs) whose nodes, users, are linked by weighted edges that reflect user similarity. It then connects the DSUGs via the users who rated items in several domains or via the users who share social connections, to create a cross-domain-user graph (CDUG). It performs Random Walk with Restarts on the CDUG to extract user nodes that are related to the starting user node on the CDUG even though they are not present in the DSUG of the starting user node. It then adds items possessed by those users to the recommendations of the starting node user. Furthermore, to extract many more user nodes, we employ a taxonomy-based similarity measure that states that users are similar if they share the same items and/or same classes. Thus we can set many suitable routes from the starting user node to other user nodes in the CDUG. An evaluation using rating datasets in two interrelated domains and social connection histories of users as extracted from a blog portal, indicates that our method identifies potentially interesting items in other domains with higher accuracy than is possible with existing CF methods.
Exploiting the Accumulated Evidence for Gene Selection in Microarray Gene Expression Data
Authors: Prat-Masramon Gabriel  , Belanche-Muñoz Lluís A.
Published: February 2025

Feature subset selection (FSS) methods play an important role for cancer classification using microarray gene expression data. In this scenario, it is extremely important to select genes by taking into account the possible interactions with other gene subsets. This paper shows that, by accumulating the evidence in favour (or against) each gene along a search process, the obtained gene subsets may constitute better solutions, either in terms of size or in predictive accuracy, or in both, at a negligible overhead in computational cost.
An AJAX-based Web Application for Disseminating Site Characterization Data
Authors: Liu Fang  , Zhou Yaping  , Jiang Mingjing
Published: February 2025

AJAX (Asynchronous JavaScript and XML) technique enables asynchronous communication between browser clients and server-side system. It shows advantages in developing responsive, interactive, and customizable web-based applications. One of the most significant users of AJAX technology, Google employs the paradigm in its many recent innovations, e.g., Google Maps. This paper presents a web-based application using Google Maps API incorporated with a customized database for disseminating data on subsurface conditions at key strong motion station sites. The data to be distributed is capsulated in a relational database, and it consists of in-situ test and laboratory test data, which provides useful information for analyzing soil profiles and characterizing the sites. A web interface, coded in JavaScript and XML, bridges the database and web clients. It presents visible data on Google Maps interface, and enables remote users to query and retrieve data from the database.
Pressure Meter Testing in Glacial Till
Authors: Shwaik Al-Zubaidi Raddi M.
Published: February 2025

Some problems of measuring undrained strength and deformation properties for glacial till are presented. These soils are stiff and have low compressibility. Because of their strong fissured character, a satisfactory sampling for laboratory testing presents great practical problems. A new pressure meter suitable for testing glacial till in situ with constant rate of membrane expansion and pore water pressure measurements are explained. By using different methods, the results of in situ horizontal total at rest stress, at rest earth pressure ratio, limit pressure, undrained shear strength and elastic modulus for four sites in Glasgow till deduced from pressure meter tests are presented.
Some design guidelines for practical argumentation systems
Authors: Dung Phan Minh  , Toni Francesca  , Mancarella Paolo
Published: February 2025

We give some design guidelines for argumentation systems. These guidelines are meant to indicate essential features of argumentation when used to support “practical reasoning”. We express the guidelines in terms of postulates. We use a notion of redundancy to provide a formal counterpart of these postulates. We study the satisfaction of these postulates in two existing argumentation frameworks: assumption-based argumentation and argumentation in classical logic.
A characterization of collective conflict for defeasible argumentation
Authors: Alsinet Teresa  , Béjar Ramón  , Godo Lluís
Published: February 2025

In this paper we define a recursive semantics for warrant in a general defeasible argumentation framework by formalizing a notion of collective (non-binary) conflict among arguments. This allows us to ensure direct and indirect consistency (in the sense of Caminada and Amgoud) without distinguishing between direct and indirect conflicts. Then, the general defeasible argumentation framework is extended by allowing to attach levels of preference to defeasible knowledge items and by providing a level-wise definition of warranted and blocked conclusions. Finally, we formalize the warrant recursive semantics for the particular framework of Possibilistic Defeasible Logic Programming, characterize the unique output program property and design an efficient algorithm for computing warranted conclusions in polynomial space.
Towards Class Diagram Algebra for Composing Data Models
Authors: Enjo Hidekazu  , Iijima Junichi
Published: February 2025

A large set of partial data models is used in designing a large information system. These partial data models provide several complementary views on the system to be developed. This however leads to a need for compositional models that are able to produce a single integrated model. These data models are often described by a class diagram of Unified Modeling Language because it is a very popular modeling language and describing a static view of a system. In this paper, we present syntax and semantics of a class diagram describing a data model. We propose a family of well-formed class diagrams as a domain of class diagram algebra and composition operations as merge and difference operations. We then show that algebraic properties as associativity, commutativity and involutivity are desired for model management to develop a large information system.
Clustering of Adolescent Criminal Offenders using Psychological and Criminological Profiles
Authors: Breitenbach Markus  , Brennan Tim  , Dieterich William  , Grudic Greg
Published: February 2025

In Criminology research the question arises if certain types of delinquents can be identified from data, and while there are many cases that can not be clearly labeled, overlapping taxonomies have been proposed in [1,2,3]. In a recent study Juvenile offenders (N = 1572) from three state systems were assessed on a battery of criminogenic risk and needs factors and their official criminal histories. Cluster analysis methods were applied. One problem we encountered is the large number of hybrid cases that have to belong to two or more classes. To eliminate these cases we propose a method that combines the results of Bagged K-Means and the consistency method [4], a semi-supervised learning technique. A manual interpretation of the results showed very interpretable patterns that were linked to existing criminologic research.
Best Practices for Predictive Analytics in B2B Financial Services
Authors: Domingos Raul  , Van de Merckt Thierry
Published: February 2025

Predictive analytics is a well known practice among corporations having business with private consumers (B2C) as a means to achieve competitive advantage. The first part of this article intends to show that corporations operating in a business to business (B2B) setting have similar conditions to use predictive analytics on their favor. Predictive analytics can be applied to solve a myriad of business problems. The solutions to solve some of these problems are well known while the resolution of other problems requires quite an amount of research and innovation. However, predictive analytics professionals tend to solve similar problems in very different ways, even those to which there are known best practices. The second part of this article uses predictive analytics applications identified in a B2B context to describe a set of best practices to solve well known problems (the “let's not re-invent the wheel” attitude) and innovative practices to solve challenging problems.
Towards the Generic Framework for Utility Considerations in Data Mining Research
Authors: Puuronen Seppo  , Pechenizkiy Mykola
Published: February 2025

Rigor data mining (DM) research has successfully developed advanced data mining techniques and algorithms, and many organizations have great expectations to take more benefit of their vast data warehouses in decision making. Even when there are some success stories the current status in practice is mainly including great expectations that have not yet been fulfilled. DM researchers have recently become interested in utility-based DM (UBDM) starting to consider some of the economic utility factors (like cost of data, cost of measurement, cost of class label and so forth), but yet many other utility factors are left outside the main directions of UBDM. The goal of this position paper is (1) to motivate researchers to consider utility from broader perspective than usually done in UBDM context and (2) to introduce a new generic framework for these broader utility considerations in DM research. Besides describing our multi-criteria utility based framework (MCUF) we present a few hypothetical examples showing how the framework might be used to consider utilities of some potential DM research stakeholders.
LetsMT! – Online Platform for Sharing Training Data and Building User Tailored Machine Translation
Authors: Vasiljevs Andrejs  , Gornostay Tatiana  , Skadins Raivis
Published: February 2025

This position paper presents the recently started European collaboration project LetsMT!. This project creates a platform that gathers public and user-provided MT training data and generates multiple MT systems by combining and prioritizing this data. The project extends the use of existing state-of-the-art SMT methods that are applied to data supplied by users to increase quality, scope and language coverage of machine translation. The paper describes the background and motivation for this work, key approaches, and the technologies used.
Fuzzy Classification of Restored MRI Images
Authors: Drummond Isabela  , Castro Ana Paula A.  , Silva José Demisio S.  , Carvalho Solon  , Sandri Sandra
Published: February 2025

This work aims at improving the performance of a supervised fuzzy classifier on noisy MRI images, by first restoring the image. The image restoration is performed here through the application of the well-known Wiener filter and of a novel ANN multiscale image restoration technique. The paper focuses on the changes in the feature space resulting from the restoration process. The tests were carried out on MRI brain images containing multiple sclerosis lesions: a synthetic image and a real one from a patient diagnosed with the disease. It was observed that the restoration process led to a compact feature space and a better kappa performance classification index, for the real MRI image and for the synthetic one when subjected to high levels of artificially added noise.
Learning to Recognize Objects in Images Using Anisotropic Nonparametric Kernels
Authors: Summers-Stay Douglas  , Aloimonos Yiannis
Published: February 2025

We present a system that makes use of image context to perform pixel-level segmentation for many object classes simultaneously. The system finds approximate nearest neighbors from the training set for a (biologically plausible) feature patch surrounding each pixel. It then uses locally adaptive anisotropic Gaussian kernels to find the shape of the class manifolds embedded in the high-dimensional space of the feature patches, in order to find the most likely label for the pixel. An iterative technique allows the system to make use of scene context information to refine its classification. Like humans, the system is able to quickly make use of new information without going through a lengthy training phase. The system provides insight into a possible mechanism for infants to quickly learn to recognize all of the classes they are presented with simultaneously, rather than having to be trained explicitly on a few classes like standard image classification algorithms.
A Formal System for Analyzing Conveyances of Property Under the Common Law
Authors: Bayern Shawn J.
Published: February 2025

This article reports on the development of a system for analyzing property transfers. Under the common law, the relationship between a transferor's language and the particular present and future interests in property that it creates can be technical and complex. This article describes a system that addresses some challenges in the law the governs property transfers.
Multilevel Data Repository for Ontological and Meta-modeling
Authors: Opmanis Mārtiņš  , Čerāns Kārlis
Published: February 2025

Metamodeling and Ontological modeling are two popular modeling approaches with their own technical tools, supporters and opponents. As a result of symbiosis of the two mentioned methodologies new metamodel is created and implemented in multilevel in-memory data repository. Repository implementation details are shown and several test- and use cases are analyzed.
Comparison of Plan-driven and Agile Project Management Approaches: Theoretical Bases for a Case Study in Estonian Software Industry
Authors: Lepmets Marion  , Nael Margus
Published: February 2025

There is evidence that Scrum could benefit from additional plan-driven practices of defined processes that address the organizational context. The question remains however how to add the plan-driven practices without losing the agility of Scrum and increasing the project performance. This paper describes the preparatory phase of the research that aims to evaluate the tailored project management process in industry. First, we compare the plan-driven project management practices derived from the process models of CMMI and ISO/IEC 15504, the PMBoK, project management literature with the Scrum practices from the case company. We then evaluate the comparison addressing the concerns of using Scrum in industry focusing on the value the plan-driven practices would have in agile environment. Finally, we propose a tailored project management process and suggest measures for evaluating the process in an industry case study.
Requirements-Level Programming for Rapid Software Evolution
Authors: Śmiałek Michał
Published: February 2025

Rapid development of evolving software systems is highly associated with the ability to react quickly to changing user requirements. This paper presents a coherent set of technologies for simplifying the path from evolving requirements to code. The most important novel element on this path is a language defined at the level of requirements (understandable for non-IT experts) that is equipped with operational semantics. This means that it is possible to translate specifications written in this language, automatically into executable code. The language also allows for easy detection of changes in requirements. This detection can be propagated down to the code structure and appropriate code parts (these that are not automatically generated) indicated for rework. It will be demonstrated that the presented approach is effective and suitable for a wide range of problem domains as opposed to domain-specific approaches. This will be shown through a case study for a typical business software system, performed with a novel tool suite.
Two Player Fair Division Problem with Uncertainty
Authors: Veski Andre  , Vohandu Leo
Published: February 2025

This paper analyses the territory fair division, problem initially posed by Hugo Steinhaus [1], by studying the solutions given by different algorithms on a large generated set of inputs for two players. Main algorithm used is Adjusted Winner, developed by S. Brams and A. Taylor [2]. We compare it to combinatorial enumeration and some algorithms proposed for experimentation by authors. Additionally we define measures to characterize the initial task and game theoretic measures to select the best solution. Moreover we extend the problem by allowing uncertainties in the players' value representation of items to be divided, based on the example of territorial division. For uncertainty management we use the belief system from Dempster-Shafer Theory [3].
Multimodal Interaction: Methods and Applications for Joint Cooperation between Humans and Cognitive Systems
Authors: Rigoll Gerhard
Published: February 2025

In this paper, we present an overview on recent advances in our work on multimodal human-machine communication between humans and technical cognitive systems in order to enable the solution of complex problems that require the joint cooperation of humans and intelligent systems to accomplish challenging tasks that can be only successfully handled if both interact in a cooperative manner. The technical system has cognitive capabilities that support an intelligent interaction with the human operator. An example for such cooperation is the joint assembly of a heavy part by a human assisted by a cognitive robot during the manufacturing process of a complex product. As will be explained, such challenges in joint cooperation occur often in intelligent manufacturing environments which provide a very rich application scenario for the successful combination of advanced multimodal human-machine communication techniques together with cognitive components for improved, cooperative interaction between technical systems and human operators.
Exhaustive Analysis of the Modular Structure of the Spliceosomal Assembly Network: A Petri Net Approach
Authors: Bortfeldt Ralf H.  , Schuster Stefan  , Koch Ina
Published: February 2025

Spliceosomes are macro-complexes involving hundreds of proteins with many functional interactions. Spliceosome assembly belongs to the key processes that enable splicing of mRNA and modulate alternative splicing. A detailed list of factors involved in spliceosomal reactions has been assorted over the past decade, but, their functional interplay is often unknown and most of the present biological models cover only parts of the complete assembly process. It is a challenging task to build a computational model that integrates dispersed knowledge and combines a multitude of reaction schemes proposed earlier.
On the Use of Laser Scans to Validate Reverse Engineering of Bony Anatomy
Authors: Anstey Joseph B.  , Smith Erin J.  , Rasquinha Brian  , Rudan John F.  , Ellis Randy E.
Published: February 2025

There is a growing body of evidence to suggest the arthritic hip is an irregularly-shaped, aspherical joint, especially in severely pathological cases. Current methods used to study the shape and motion of the hip in-vivo, are invasive and impractical. This study aimed to assess whether a plastic model of the hip joint can be accurately made from a pelvic CT scan. A cadaver hemi-pelvis was CT imaged and segmented from which a 3D plastic model of the proximal femur and hemi-pelvis were fabricated using rapid-prototyping. Both the plastic model and the cadaver were then imaged using a high-resolution laser scanner. A three-way shape analysis was performed to compare the goodness-of-fit between the cadaver, image segmentation, and the plastic model. Overall, we obtained sub-millimeter fit accuracy between all three hip representations. Shape fit was least favorable in areas where the boundary between cartilage and bone is difficult to distinguish. We submit that rapid-prototyping is an accurate and efficient mechanism for obtaining 3D specimens as a means to further study the irregular geometry of the hip.
A Software Framework for Multimodal Interactive Simulations (SoFMIS)
Authors: Halic Tansel  , Venkata Sreekanth A.  , Sankaranarayanan Ganesh  , Lu Zhonghua  , Ahn Woojin  , De Suvranu
Published: February 2025

The development of a multimodal interactive simulation is a very elaborate task due to the various complex software components involved, which run simultaneously at very high rates with maximum CPU load. In this work, we propose a multimodal parallel simulation framework called SoFMIS to create rapid interactive simulations such as surgical simulations. Our framework offers great flexibility and customization allowing simulation developers and researchers to concentrate on the simulation logic rather than component development.
Validation of Robotic Surgery Simulator (RoSS)
Authors: Kesavadas Thenkurussi  , Stegemann Andrew  , Sathyaseelan Gughan  , Chowriappa Ashirwad  , Srimathveeravalli Govindarajan  , Seixas-Mikelus Stéfanie  , Chandrasekhar Rameella  , Wilding Gregory  , Guru Khurshid
Published: February 2025

Recent growth of daVinciTMRobotic Surgical System as a minimally invasive surgery tool has led to a call for better training of future surgeons. In this paper, a new virtual reality simulator, called RoSS is presented. Initial results from two studies – face and content validity, are very encouraging. 90% of the cohort of expert robotic surgeons felt that the simulator was excellent or somewhat close to the touch and feel of the daVinci console. Content validity of the simulator received 90% approval in some cases. These studies demonstrate that RoSS has the potential of becoming an important training tool for the daVinci surgical robot.
Registration Stability of Physical Templates in Hip Surgery
Authors: Kunz Manuela  , Rudan John F.  , Wood Gavin C.A.  , Ellis Randy E.
Published: February 2025

We tested the registration stability of individualized templates in a consecutive study with 80 patients undergoing hip-resurfacing surgery. These templates physically encode registration and navigation parameters but do not require a computer during the actual surgery. The surgical target was the placement of the femoral guidance pin during hip resurfacing, which is a difficult and highly variable task using conventional instruments. The drill trajectory for the guidance pin of the femoral component was planned on a 3D computer model of the femur derived from a preoperative computed tomography (CT) scan. A surface-matched drilling template was designed to perform mechanical registration on the bone surface and had a hole for the drill guide; the template was created using a rapid prototyping machine. Intraoperatively, the individualized template was positioned on the patient anatomy and the pin was drilled into the femoral neck. The final achieved pin orientation and position were measured using an optoelectronic CT-based navigation system. The measured mean deviation between planned and actual central pin alignment of 0.05° in valgus and 2.8° in anteversion shows that the proposed individualized templates for hip resurfacing have reliable registration.
Simulation and Modeling of Metamorphopsia with a Deformable Amsler Grid
Authors: Martin-Gonzalez Anabel  , Lanzl Ines  , Khoramnia Ramin  , Navab Nassir
Published: February 2025

A method to simulate and model metamorphopsia by means of a deformable Amsler grid is proposed. The interactively deformable grid is based on cubic B-splines to obtain a locally controlled deformation. By simulating metamorphopsia on normal sight volunteers, acquisition of a correction percentage is possible as a result of analyzing the magnitude of the simulated distortion and the applied correction model. The correction percentage obtained is 75.78% (7.36% standard deviation). This can express the feasible correction rate with the guidance of the patient qualitative feedback. The present work is motivated by the idea of obtaining a correction model of a patient with metamorphopsia and to implement this model into a head-mounted display to compensate the patient's deformation in the near future.
Pneumoperitoneum Technique Simulation in Laparoscopic Surgery on Lamb Liver Samples and 3D Reconstruction
Authors: Martínez-Martínez F.  , Rupérez M.J.  , Lago M.A.  , López-Mir F.  , Monserrat C.  , Alcañíz M.
Published: February 2025

In this paper, a procedure to experimentally simulate the behavior of the liver when the pneumoperitoneum technique is applied in laparoscopic surgery is presented, as well as methodology to make the comparison of each sample before and after insufflating the gas. This comparison is carried out using the 3D reconstruction of the volume from the CT images when either pneumoperitoneum is applied and when it is not. This methodology has showed that there are perceptible changes of volume when the pneumoperitoneum is applied.
Virtual Reality Haptic Human Dissection
Authors: Needham Caroline  , Wilkinson Caroline  , Soames Roger
Published: February 2025

This project aims to create a three-dimensional digital model of the human hand and wrist which can be virtually ‘dissected’ through a haptic interface. Tissue properties will be added to the various anatomical structures to replicate a realistic look and feel. The project will explore the role of the medical artist and investigate the cross-discipline collaborations required in the field of virtual anatomy. The software will be used to train anatomy students in dissection skills before experience on a real cadaver. The effectiveness of the software will be evaluated and assessed both quantitatively as well as qualitatively.
Manual Accuracy in Comparison with a Miniature Master Slave Device – Preclinical Evaluation for Ear Surgery
Authors: Runge A.  , Hofer M.  , Dittrich E.  , Neumuth T.  , Haase R.  , Strauss M.  , Dietz A.  , Lüth T.  , Strauss G.
Published: February 2025

Manual accuracy in microsurgery is reduced by tremor and limited access. A surgical approach through the middle ear also puts delicate structures at risk, while the surgeon is often working at an unergonomic position. At this point a micromanipulator could have a positive influence. A system was developed to measure “working accuracy”, time and precision during manipulation in the middle ear. 10 ENT-surgeons simulated a perforation of the stapedial footplate on a modified 3D print of a human skull in a mock OR. Each trial was repeated more than 200 times aiming manually and using a micro-manipulator. Data of over 4000 measurements was tested and graphically processed. Work strain was evaluated with a questionnaire.
Are Commercially Available Simulators Durable Enough for Classroom Use?
Authors: Salud Jonathan C.  , Blossfield Iannitelli Katherine  , Salud Lawrence H.  , Pugh Carla M.
Published: February 2025

Our efforts show that commercially available simulators can be modified to affect realism and durability.
Use of Sensor Technology to Explore the Science of Touch
Authors: Salud Lawrence H.  , Pugh Carla M.
Published: February 2025

Two, world-renown researchers in the science of touch (Klatzky and Lederman) have shown that there are a set of reproducible and subconscious maneuvers that humans use to explore objects. Force measuring sensors may be used to electronically identify and quantify these maneuvers. Two sensored silicone breast models were configured to represent two different clinical presentations. One-hundred clinicians attending a local breast cancer meeting performed clinical breast examinations on the models, and their performance was captured using sensor-based data acquisition technology. We have found that Klatzy and Lederman's previously defined touch maneuvers are used during the clinical breast examination and can be identified and quantified for the first time using sensor technology.
Comparison of a Disposable Bougie versus a Newly Designed Malleable Bougie in the Intubation of a Difficult Manikin Airway
Authors: Boedeker Ben H.  , Bernhagen Mary  , Miller David J.  , Murray W. Bosseau
Published: February 2025

The endotracheal bougie is used for difficult intubations when only a minimal glottic view is obtained. Standard bougies are designed for use during direct, line-of-sight viewing of the glottic opening. With videolaryngoscopy, intubators “see around the corner”, thus requiring a bougie which can be shaped to follow a significant curve. A malleable bougie with an imbedded internal wire was created to enable intubators to shape the curve to best fit a difficult airway. This pilot study examined the malleable bougie compared to the SunMedTMbougie in a simulated difficult airway intubation using video laryngoscopy.
Single and Multi-User Virtual Patient Design in the Virtual World
Authors: Taylor D.  , Patel V.  , Cohen D.  , Aggarwal R.  , Kerr K.  , Sevdalis N.  , Batrick N.  , Darzi A.
Published: February 2025

This researchAcknowledgements: Phase 1 was supported by the London Deanery under their Simulation Technology-enhanced Learning Initiative (STeLI). Phase 2 was supported by funding from the Health Protection Agency. Aggarwal and Sevdalis are supported by the UK's National Institute for Health Research through a Clinician Scientist award and the Imperial Centre for Patient Safety and Service Quality, respectively.
Towards the Visualization of Spiking Neurons in Virtual Reality
Authors: von Kapri Anette  , Rick Tobias  , Potjans Tobias C.  , Diesmann Markus  , Kuhlen Torsten
Published: February 2025

This paper presents a prototype that addresses the visualization of the microscopic activity structure in the mammalian brain. Our approach displays the spiking behaviour of neurons in multiple layers based on large-scale simulations of the cortical microcircuit. We will apply this visualization to the activity of brain-scale simulations by coupling the microscopic structure with the macroscopic level. Thereby, we hope to convey an intuitive understanding of the concise interaction and the activity flow of pairs of distant brain areas.
Validation of a Virtual Preoperative Evaluation Clinic: A Pilot Study
Authors: Zetterman Corey V.  , Sweitzer Bobbie J.  , Webb Brad  , Barak-Bernhagen Mary A.  , Boedeker Ben H.
Published: February 2025

Patients scheduled for surgery at the Omaha VA Medical Center were evaluated preoperatively via telemedicine. Following the examination, patients filled out a 15 item, 5 point Likert scale questionnaire regarding their opinion of preoperative evaluation in a VTC format. Evaluations were performed under the direction of nationally recognized guidelines and recommendations of experts in the field of perioperative medicine and were overseen by a staff anesthesiologist from the Omaha VA Medical Center. No significant difficulties were encountered by the patient or the evaluator regarding the quality of the audio/visual capabilities of the VTC link and its ability to facilitate preoperative evaluation. 87.5% of patients felt that virtual evaluation would save them travel time; 87.5% felt virtual evaluation could save them money; 7.3 % felt uncomfortable using the VTC link; 12.2 % felt the virtual evaluation took longer than expected; 70.7 % preferred to be evaluated via VTC link; 21.9 % were undecided; 9.7% felt they would rather be evaluated face-to-face with 26.8 % undecided; 85.0 % felt that teleconsultation was as good as being seen at the Omaha surgical evaluation unit; 7.5 % were undecided. Our study has shown that effective preoperative evaluation can be performed using a virtual preoperative evaluation clinic; patients are receptive to the VTC format and, in the majority of cases, prefer it to face-to-face evaluation.
Maintaining Forward View of the Surgical Site for Best Endoscopic Practice
Authors: Zheng Bin  , Cassera Maria A.  , Swanström Lee L.  , Meneghetti Adam  , Panton Neely O.N.  , Qayumi Karim A.
Published: February 2025

Endoscopic surgery performed through patients' natural orifices (NOTES procedures) often require some degree of retroflexion of the operating system. This can cause a misalignment between the displayed image and the actual work plane, leading to performance difficulties. This study investigated the impact of retroflexion on task performance in a simulated environment. Surgeons were required to perform an aiming and pointing task under two experimental conditions: forward-view vs. retroflexed-view. Results showed that both expert and novice surgeons required significantly longer time for completing the task when the scope was retroflexed, compared to when the scope faced forwards. Results address the importance of careful selection of the surgical approach to avoid image retroflexion. Further analysis revealed that the novices were more vulnerable than experts to image distortion with the retroflexed view. This addresses the necessity for surgeons to go through extensive endoscopic training to overcome the visual-motor challenges before they can perform NOTES procedures safely and effectively.
Longitudinal Analysis on Utilization of Medical Document Management System in a Hospital with EPR Implementation
Authors: Kuwata Shigeki  , Yamada Hitomi  , Park Keunsik
Published: February 2025

Document management systems (DMS) have widespread in major hospitals in Japan as a platform to digitize the paper-based records being out of coverage by EPR. This study aimed to examine longitudinal trends of actual use of DMS in a hospital in which EPR had been in operation, which would be conducive to planning the further information management system in the hospital. Degrees of utilization of electronic documents and templates with DMS were analyzed based on data extracted from a university-affiliated hospital with EPR. As a result, it was found that the number of electronic documents as well as scanned documents circulating at the hospital tended to increase. The result indicated that replacement of paper-based documents with electronic documents did not occur. Therefore it was anticipated that the need for DMS would continue to increase in the hospital. The methods used this study to analyze the trend of DMS utilization would be applicable to other hospitals with with a variety of DMS implementation, such as electronic storage by scanning documents or paper preservation that is compatible with EPR.
EHR Strategy: Top Down, Bottom Up or Middle Out?
Authors: Bowden Thomas C.
Published: February 2025

Around the world a number of countries have made a concerted effort to embed Information and Communications Technology (ICT) within their health systems. It is widely acknowledged that the successful application of ICT to health systems can bring about significant benefits. A number of areas commonly singled out for improvement include: coordination of care; improved medication management; and streamlining the transfer of a patient's care from one healthcare provider to another. There are also perceived cost-benefits including reduced duplication of services and improved service utilization. Countries across the world have chosen many and varied paths to automating their health systems. Health systems are intrinsically very complicated and changing rapidly. Because they represent a high proportion of government expenditure, it is important to understand what is being achieved by each of the broad approaches that are being taken.
Automation Bias – A Hidden Issue for Clinical Decision Support System Use
Authors: Goddard Kate  , Roudsari Abdul  , Wyatt Jeremy C.
Published: February 2025

Automation bias – the tendency to over-rely on automation – has been studied in a variety of academic fields. Clinical Decision Support Systems aim to benefit the clinical decision making process. Although most research shows overall improved performance with use, there is often a failure to recognize the new errors that CDSS can introduce, and the healthcare field has a gap in this research. This paper outlines some of the most compelling theoretical factors in the literature involved in automation bias, and builds a simple model to be tested empirically. Ultimately, this will uncover the mechanisms by which this bias operates and help CDSS producers and healthcare practitioners optimize the medical decision making process.