Search results for: electronic clinical decision support systems

Authors: Hitham Yami

Abstract:

This study will focus primarily on assessing the availability requirements of the electronic management of oil companies in Libya, and the mean objectives of the research applying electronic management and make recommendations and steps to approach electronic management. There are limited research and statistical analysis to support electronic management in Libyan companies. The groundwork for the proposed approach is to develop independent variables and the dependent variables to be restructured after it Alntra side of the field and the side to get the data to achieve the desired results and solving the problem faced by the Libyan Oil Corporation. All these strategies are proposed to achieve the goal, and solving Libyan oil installations.

Keywords: oil company’s revenue, independent variables, electronic management, Libyan oil corporation

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Authors: Mansour N. Jadid

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This paper describes the implementation of a GIS to provide decision support for successfully monitoring the movements and storage of materials, hence ensuring that finished products travel from the point of origin to the destination construction site through the supply-chain management (SCM) system. This system ensures the efficient operation of suppliers, manufacturers, and distributors by determining the shortest path from the point of origin to the final destination to reduce construction costs, minimize time, and enhance productivity. These systems are essential to the construction industry because they reduce costs and save time, thereby improve productivity and effectiveness. This study describes a typical supply-chain model and a geographical information system (GIS)-based SCM that focuses on implementing an electronic document management system, which maps the application framework to integrate geodetic support with the supply-chain system. This process provides guidance for locating the nearest suppliers to fill the information needs of project members in different locations. Moreover, this study illustrates the use of a GIS-based SCM as a collaborative tool in innovative methods for implementing Web mapping services, as well as aspects of their integration by generating an interactive GIS for the construction industry platform.

Keywords: construction, coordinate, engineering, GIS, management, map

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Authors: D. Pérez, M. M. E. Alemany

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In this work a Framework to model the Supply Chain (SC) Collaborative Planning (CP) Process is proposed, and particularly its Decisional view. The main Framework contributions with regards to previous related works are the following, 1) the consideration of not only the Decision view, the most important one due to the Process type, but other additional three views which are the Physical, Organisation and Information ones, closely related and complementing the Decision View, 2) the joint consideration of two interdependence types, the Temporal (among Decision Centres belonging to different Decision Levels) and Spatial (among Decision Centres belonging to the same Decision Level) to support the distributed Decision-Making process in SC where several decision Centres interact among them in a collaborative manner.

Keywords: collaborative planning, decision view, distributed decision-making, framework

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Authors: Yavuz Unal, Kemal Polat, H. Erdinc Kocer

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In this study, a decision support system comprising three stages has been proposed to detect the disc abnormalities of the lumbar region. In the first stage named the feature extraction, T2-weighted sagittal and axial Magnetic Resonance Images (MRI) were taken from 55 people and then 27 appearance and shape features were acquired from both sagittal and transverse images. In the second stage named the feature weighting process, k-means clustering based feature weighting (KMCBFW) proposed by Gunes et al. Finally, in the third stage named the classification process, the classifier algorithms including multi-layer perceptron (MLP- neural network), support vector machine (SVM), Naïve Bayes, and decision tree have been used to classify whether the subject has lumbar disc or not. In order to test the performance of the proposed method, the classification accuracy (%), sensitivity, specificity, precision, recall, f-measure, kappa value, and computation times have been used. The best hybrid model is the combination of k-means clustering based feature weighting and decision tree in the detecting of lumbar disc disease based on both sagittal and axial MR images.

Keywords: lumbar disc abnormality, lumbar MRI, lumbar spine, hybrid models, hybrid features, k-means clustering based feature weighting

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Authors: Mitra Ghiasi, Roghayeh Ghorbani Bousari

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Nowadays, the aim of the organizations is to gain sustainable competitive. So, developing their intellectual capital, encouraging innovation, increasing suitable performance can be done by knowledge management. Knowledge turns into science if knowledge is used to improve decision making, decision quality and make effective decisions. The current research intends to investigate the relationship between cybernetics and knowledge management from the perspective of users who are members of electronic discussion groups (ALA, ALIA). The research methodology is survey method, and it is a type of correlation research. Cybernetics and knowledge management questionnaires used for collecting data. The questionnaire that was designed in electronic format, distributed among two electronic discussion groups during 30 days and completed by 100 members of each electronic discussion groups. The finding of this research showed that although cybernetics has an impact on knowledge management, there is no significant difference between the ALA and ALIA user's view regard to effect of cybernetics on knowledge management. The results also indicated that this conceptual model is consistent with the data collected from the sample.

Keywords: ALA discussion group, ALIA discussion group, cybernetics, knowledge management

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Authors: Ozgu Turgut

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Water scarcity is a problem for many regions which requires immediate action, and solutions cannot be postponed for a long time. It is known that farming consumes a significant portion of usable water. Although in recent years, the efforts to make the transition to dripping or spring watering systems instead of using surface watering started to pay off. It is also known that this transition is not necessarily translated into an increase in the capacity dedicated to other water consumption channels such as city water or power usage. In order to control and allocate the water resource more purposefully, new watering systems have to be used with monitoring abilities that can limit the usage capacity for each farm. In this study, a decision support model which relies on a bi-objective stochastic linear optimization is proposed, which takes crop yield and price volatility into account. The model generates annual planting plans as well as water usage limits for each farmer in the region while taking the total value (i.e., profit) of the overall harvest. The mathematical model is solved using the L-shaped method optimally. The decision support model can be especially useful for regional administrations to plan next year's planting and water incomes and expenses. That is why not only a single optimum but also a set of representative solutions from the Pareto set is generated with the proposed approach.

Keywords: decision support, farming, water, tactical planning, optimization, stochastic, pareto

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Authors: Chitra Rajagopal, Indra Deo Kumar, Ruchi Joshi, Binoy Bhargavan

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Role of fighter planes in modern network centric military warfare scenarios has changed significantly in the recent past. New generation fighter planes have multirole capability of engaging both air and ground targets with high precision. Multirole aircraft undertakes missions such as Air to Air combat, Air defense, Air to Surface role (including Air interdiction, Close air support, Maritime attack, Suppression and Destruction of enemy air defense), Reconnaissance, Electronic warfare missions, etc. Designers have primarily focused on development of technologies to enhance the combat performance of the fighter planes and very little attention is given to human factor aspects of technologies. Unique physical and psychological challenges are imposed on the pilots to meet operational requirements during these missions. Newly evolved technologies have enhanced aircraft performance in terms of its speed, firepower, stealth, electronic warfare, situational awareness, and vulnerability reduction capabilities. This paper highlights the impact of emerging technologies on human factors for various military operations and missions. Technologies such as ‘cooperative knowledge-based systems’ to aid pilot’s decision making in military conflict scenarios as well as simulation technologies to enhance human performance is also studied as a part of research work. Current and emerging pilot protection technologies and systems which form part of the integrated life support systems in new generation fighter planes is discussed. System safety analysis application to quantify the human reliability in military operations is also studied.

Keywords: combat effectiveness, emerging technologies, human factors, systems safety analysis

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Authors: Phang Moon Leng

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Automated Early Warning Scores is a newly developed clinical decision tool that is used to streamline and improve the process of obtaining a patient’s vital signs so a clinical decision can be made at an earlier stage to prevent the patient from further deterioration. This technology provides immediate update on the score and clinical decision to be taken based on the outcome. This paper aims to study the use of an automated early warning score system on whether the technology has assisted the hospital in early detection and escalation of clinical condition and improve patient outcome. The hospital adopted the Modified Early Warning Scores (MEWS) Scoring System and MEWS Clinical Response into Philips IntelliVue Guardian Automated Early Warning Score equipment and studied whether the process has been leaned, whether the use of technology improved the usage & experience of the nurses, and whether the technology has improved patient care and outcome. It was found the steps required to obtain vital signs has been significantly reduced and is used more frequently to obtain patient vital signs. The number of deaths, and length of stay has significantly decreased as clinical decisions can be made and escalated more quickly with the Automated EWS. The automated early warning score equipment has helped improve work efficiency by removing the need for documenting into patient’s EMR. The technology streamlines clinical decision-making and allows faster care and intervention to be carried out and improves overall patient outcome which translates to better care for patient.

Keywords: automated early warning score, clinical quality and safety, patient safety, medical technology

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Authors: Ashwin Belle, Bryce Benson, Mark Salamango, Fadi Islim, Rodney Daniels, Kevin Ward

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A reliable, real-time, and non-invasive system that can identify patients at risk for hemodynamic instability is needed to aid clinicians in their efforts to anticipate patient deterioration and initiate early interventions. The purpose of this pilot study was to explore the clinical capabilities of a real-time analytic from a single lead of an electrocardiograph to correctly distinguish between rapid response team (RRT) activations due to hemodynamic (H-RRT) and non-hemodynamic (NH-RRT) causes, as well as predict H-RRT cases with actionable lead times. The study consisted of a single center, retrospective cohort of 21 patients with RRT activations from step-down and telemetry units. Through electronic health record review and blinded to the analytic’s output, each patient was categorized by clinicians into H-RRT and NH-RRT cases. The analytic output and the categorization were compared. The prediction lead time prior to the RRT call was calculated. The analytic correctly distinguished between H-RRT and NH-RRT cases with 100% accuracy, demonstrating 100% positive and negative predictive values, and 100% sensitivity and specificity. In H-RRT cases, the analytic detected hemodynamic deterioration with a median lead time of 9.5 hours prior to the RRT call (range 14 minutes to 52 hours). The study demonstrates that an electrocardiogram (ECG) based analytic has the potential for providing clinical decision and monitoring support for caregivers to identify at risk patients within a clinically relevant timeframe allowing for increased vigilance and early interventional support to reduce the chances of continued patient deterioration.

Keywords: critical care, early warning systems, emergency medicine, heart rate variability, hemodynamic instability, rapid response team

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Authors: K. Marciniak, M. Owoc

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Managers as decision-makers present in different sectors should be supported in efficient and more and more sophisticated way. There are huge number of software tools developed for such users starting from simple registering data from business area – typical for operational level of management – up to intelligent techniques with delivering knowledge - for tactical and strategic levels of management. There is a big challenge for software developers to create intelligent management dashboards allowing to support different decisions. In more advanced solutions there is even an option for selection of intelligent techniques useful for managers in particular decision-making phase in order to deliver valid knowledge-base. Such a tool (called Intelligent Dashboard for SME Managers–InKOM) is prepared in the Business Intelligent framework of Teta products. The aim of the paper is to present solutions assumed for InKOM concerning on management of stored knowledge bases offering for business managers. The paper is managed as follows. After short introduction concerning research context the discussed supporting managers via information systems the InKOM platform is presented. In the crucial part of paper a process of knowledge transformation and validation is demonstrated. We will focus on potential and real ways of knowledge-bases acquiring, storing and validation. It allows for formulation conclusions interesting from knowledge engineering point of view.

Keywords: business intelligence, decision support systems, knowledge management, knowledge transformation, knowledge validation, managerial systems

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Authors: D. Moser, D. Pinto, A. Cipriano

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A Disaster Management System (DMS) for countries with different disasters is very important. In the world different disasters like earthquakes, tsunamis, volcanic eruption, fire or other natural or man-made disasters occurs and have an effect on the population. It is also possible that two or more disasters arisen at the same time, this means to handle multi-risk situations. To handle such a situation a Decision Support System (DSS) based on multiagents is a suitable architecture. The most known DMSs deal with one (in the case of an earthquake-tsunami combination with two) disaster and often with one particular disaster. Nevertheless, a DSS helps for a better realtime response. Analyze the existing systems in the literature and expand them for multi-risk disasters to construct a well-organized system is the proposal of our work. The here shown work is an approach of a multi-risk system, which needs an architecture, and well-defined aims. In this moment our study is a kind of case study to analyze the way we have to follow to create our proposed system in the future.

Keywords: decision support system, disaster management system, multi-risk, multiagent system

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Authors: Murat Durucu

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Glaucoma is a condition of irreversible blindness, early diagnosis and appropriate interventions to make the patients able to see longer time. In this study, it addressed that the importance of developing a decision support system for glaucoma diagnosis. Glaucoma occurs when pressure happens around the eyes it causes some damage to the optic nerves and deterioration of vision. There are different levels ranging blindness of glaucoma disease. The diagnosis at an early stage allows a chance for therapies that slows the progression of the disease. In recent years, imaging technology from Heidelberg Retinal Tomography (HRT), Stereoscopic Disc Photo (SDP) and Optical Coherence Tomography (OCT) have been used for the diagnosis of glaucoma. This better accuracy and faster imaging techniques in response technique of OCT have become the most common method used by experts. Although OCT images or HRT precision and quickness, especially in the early stages, there are still difficulties and mistakes are occurred in diagnosis of glaucoma. It is difficult to obtain objective results on diagnosis and placement process of the doctor's. It seems very important to develop an objective decision support system for diagnosis and level the glaucoma disease for patients. By using OCT images and pattern recognition systems, it is possible to develop a support system for doctors to make their decisions on glaucoma. Thus, in this recent study, we develop an evaluation and support system to the usage of doctors. Pattern recognition system based computer software would help the doctors to make an objective evaluation for their patients. It is intended that after development and evaluation processes of the software, the system is planning to be serve for the usage of doctors in different hospitals.

Keywords: decision support system, glaucoma, image processing, pattern recognition

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Authors: Hamna Hamid, Kashmala Zaman

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The aim of this study was to evaluate the relationship between self-efficacy, resilience, and social support among clinical psychologists, counselors, and teachers of special schools. The study also assesses the gender differences in self-efficacy, resilience, social support, and vicarious trauma and also vicarious trauma differences among three professions, i.e., clinical psychologists, counselors, and teachers of special schools. A sample of 150 women and 97 men were handed out a set questionnaire to complete: a General Self-Efficacy Scale, Brief Resilience Scale, Multidimensional Scale of Perceived Social Support, and Vicarious Trauma Scale. Results showed that there is a significant negative correlation between self-efficacy, resilience, and vicarious trauma. Women experience higher levels of vicarious trauma as compared to men. At the same time, clinical psychologists and counselors experience higher levels of vicarious trauma as compared to teachers of special schools. The moderation effect of social support is not significant towards resilience and vicarious trauma.

Keywords: self-efficacy, resilience, vicarious-trauma social-support, social support

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Authors: A. Ashraff

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The increasing importance of the web as a medium for electronic and business transactions has served as a catalyst or rather a driving force for the introduction and implementation of recommender systems. Recommender Systems play a major role in processing and analyzing thousands of data rows or reviews and help humans make a purchase decision of a product or service. It also has the ability to predict whether a particular user would rate a product or service based on the user’s profile behavioral pattern. At present, Recommender Systems are being used extensively in every domain known to us. They are said to be ubiquitous. However, in the field of recruitment, it’s not being utilized exclusively. Recent statistics show an increase in staff turnover, which has negatively impacted the organization as well as the employee. The reasons being company culture, working flexibility (work from home opportunity), no learning advancements, and pay scale. Further investigations revealed that there are lacking guidance or support, which helps a job seeker find the company that will suit him best, and though there’s information available about companies, job seekers can’t read all the reviews by themselves and get an analytical decision. In this paper, we propose an approach to study the available review data on IT companies (score their reviews based on user review sentiments) and gather information on job seekers, which includes their Psychometric evaluations. Then presents the job seeker with useful information or rather outputs on which company is most suitable for the job seeker. The theoretical approach, Algorithmic approach and the importance of such a system will be discussed in this paper.

Keywords: psychometric tests, recommender systems, sentiment analysis, hybrid recommender systems

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Authors: T. Penkova, A. Korobko, V. Nicheporchuk, L. Nozhenkova, A. Metus

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This paper presents an approach of on-line control of the state of technosphere and environment objects based on the integration of Data Warehouse, OLAP and Expert systems technologies. It looks at the structure and content of data warehouse that provides consolidation and storage of monitoring data. There is a description of OLAP-models that provide a multidimensional analysis of monitoring data and dynamic analysis of principal parameters of controlled objects. The authors suggest some criteria of emergency risk assessment using expert knowledge about danger levels. It is demonstrated now some of the proposed solutions could be adopted in territorial decision making support systems. Operational control allows authorities to detect threat, prevent natural and anthropogenic emergencies and ensure a comprehensive safety of territory.

Keywords: decision making support systems, emergency risk assessment, natural and anthropogenic safety, on-line control, territory

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Authors: Idris Lawal

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Electronic payment system is simply a payment or monetary transaction made over the internet or a network of computers. This study was carried out in order to assess how electronic payment system has impacted on banks service delivery, to examine the efficiency of electronic payment system in Nigeria and to determine the level of customer's satisfaction as a direct result of the deployment of electronic payment systems. It is an empirical study conducted using structured questionnaire distributed to officials and customers of Access Bank plc. Chi-square(x2) was adopted for the purpose of data analysis. The result of the study showed that the development of electronic payment system offer great benefit to bank customers including improved services, reduced turn-around time, ease of banking transaction, significant cost saving etc. The study recommends that customer protection laws should be properly put in place to safeguard the interest of end users of e-payment instruments.

Keywords: bank, electronic payment systems, service delivery, customer's satisfaction

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Authors: F. Felipe

Abstract:

Air Defense Systems contain high-value assets that are expected to fulfill their mission for several years - in many cases, even decades - while operating in a fast-changing, technology-driven environment. Thus, it is paramount that decision-makers can assess how effective an Air Defense System is in the face of new developing threats, as well as to identify the bottlenecks that could jeopardize the security of the airspace of a country. Given the broad extent of activities and the great variety of assets necessary to achieve the strategic objectives, a systems approach was taken in order to delineate the core requirements and the physical architecture of an Air Defense System. Then, value-focused thinking helped in the definition of the measures of effectiveness. Furthermore, analytical methods were applied to create a formal structure that preliminarily assesses such measures. To validate the proposed methodology, a powerful simulation was also used to determine the measures of effectiveness, now in more complex environments that incorporate both uncertainty and multiple interactions of the entities. The results regarding the validity of this methodology suggest that the approach can support decisions aimed at enhancing the capabilities of Air Defense Systems. In conclusion, this paper sheds some light on how consolidated approaches of Systems Engineering and Operations Research can be used as valid techniques for solving problems regarding a complex and yet vital matter.

Keywords: air defense, effectiveness, system, simulation, decision-support

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Authors: Hamna Hamid, Kashmala Zaman

Abstract:

The aim of this study was to evaluate the relationship between self-efficacy, resilience and social support among clinical psychologists, counselors and teachers of special schools. The study also assesses the gender differences on self-efficacy, resilience, social support and vicarious trauma and also vicarious trauma differences among three professions i.e. clinical psychologists, counselors and teachers of special schools. A sample of 150 women and 97 men were handed out a set questionnaire to complete: General Self-Efficacy Scale, Brief Resilience Scale, Multidimensional Scale of Perceived Social Support and Vicarious Trauma Scale. Results showed that there is significant negative correlation between self-efficacy, resilience and vicarious trauma. Women experiences higher levels of vicarious trauma as compared to men. While clinical psychologists and counselors experience higher levels of vicarious trauma as compared to teachers of special schools. Moderation effect of social support is not significant towards resilience and vicarious trauma.

Keywords: self-efficacy, resilience, vicarious trauma, social-support

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Authors: Roberta Gentry

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Electronic mentoring is defined as a relationship between a mentor and a mentee using computer mediated communication (CMC) that is intended to develop and improve mentee’s skills, confidence, and cultural understanding. This session will increase knowledge about electronic mentoring, its uses, and outcomes. The research behind electronic mentoring and descriptions of existing programs will also be shared.

Keywords: electronic mentoring, mentoring, beginning special educators, education

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Authors: Ismail El Gayar, Ossama Ismail, Yousri El Gamal

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This paper presented a technique to solve one of the transportation problems that faces us in real life which is the Bus Scheduling Problem. Most of the countries using buses in schools, companies and traveling offices as an example to transfer multiple passengers from many places to specific place and vice versa. This transferring process can cost time and money, so we build a decision support system that can solve this problem. In this paper, a genetic algorithm with the shortest path technique is used to generate a competitive solution to other well-known techniques. It also presents a comparison between our solution and other solutions for this problem.

Keywords: bus scheduling problem, decision support system, genetic algorithm, shortest path

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Authors: Lucy W. Mburu, Richard Karanja, Simon N. Mwendia

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Over recent years, learners have experienced a constant need to access on demand knowledge that is fully aligned with the paradigm of cloud computing. As motivated by the global sustainable development goal to ensure inclusive and equitable learning opportunities, this research has developed a framework hinged on the knowledge-as-a-service architecture that utilizes knowledge from ambient learning systems. Through statistical analysis and decision tree modeling, the study discovers influential variables for ambient learning among university students. The main aim is to generate a platform for disseminating and exploiting the available knowledge to aid the learning process and, thus, to improve educational support on the ambient learning system. The research further explores how collaborative effort can be used to form a knowledge network that allows access to heterogeneous sources of knowledge, which benefits knowledge consumers, such as the developers of ambient learning systems.

Keywords: actionable knowledge, ambient learning, cloud computing, decision trees, knowledge as a service

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Authors: Rawan A. Abdelrazeq, Ahmed M. Khalafallah, Nabil A. Kartam

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Selection of competent contractors for construction projects is usually accomplished through competitive bidding or negotiated contracting in which the contract bid price is the basic criterion for selection. The evaluation of contractor’s safety performance is still not a typical criterion in the selection process, despite the existence of various safety prequalification procedures. There is a critical need for practical and automated systems that enable owners and decision makers to evaluate contractor safety performance, among other important contractor selection criteria. These systems should ultimately favor safety-conscious contractors to be selected by the virtue of their past good safety records and current safety programs. This paper presents an exploratory sequential mixed-methods approach to develop a framework for an automated decision support system that evaluates contractor safety performance based on a multitude of indicators and metrics that have been identified through a comprehensive review of construction safety research, and a survey distributed to domain experts. The framework is developed in three phases: (1) determining the indicators that depict contractor current and past safety performance; (2) soliciting input from construction safety experts regarding the identified indicators, their metrics, and relative significance; and (3) designing a decision support system using relational database models to integrate the identified indicators and metrics into a system that assesses and rates the safety performance of contractors. The proposed automated system is expected to hold several advantages including: (1) reducing the likelihood of selecting contractors with poor safety records; (2) enhancing the odds of completing the project safely; and (3) encouraging contractors to exert more efforts to improve their safety performance and practices in order to increase their bid winning opportunities which can lead to significant safety improvements in the construction industry. This should prove useful to decision makers and researchers, alike, and should help improve the safety record of the construction industry.

Keywords: construction safety, contractor selection, decision support system, relational database

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Authors: Jun-Ho Park, Kwang-Woo Nam, Seung-Mo Hong, Tae-Heon Moon, Sang-Ho Lee, Youn-Taik Leem

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The aim of this study was to build ‘Ubi-Net’, a decision-making support system for systematic establishment in U-City planning. We have experienced various urban problems caused by high-density development and population concentrations in established urban areas. To address these problems, a U-Service contributes to the alleviation of urban problems by providing real-time information to citizens through network connections and related information. However, technology, devices, and information for consumers are required for systematic U-Service planning in towns and cities where there are many difficulties in this regard, and a lack of reference systems. Thus, this study suggests methods to support the establishment of sustainable planning by providing comprehensive information including IT technology, devices, news, and social networking services(SNS) to U-City planners through intelligent searches. In this study, we targeted Smart U-Parking Planning to solve parking problems in an ‘old’ city. Through this study, we sought to contribute to supporting advances in U-Space and the alleviation of urban problems.

Keywords: desigin and decision support system, smart u-parking planning, social network analysis, urban engineering

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Authors: Peyman Rezaei Hachesu, Vahideh Zareh Gavgani, Zahra Salahzadeh

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To survey the attitudes, awareness, and practice of Evidence Based Medicine (EBM), and to determine the barriers that influence apply’ EBM in therapeutic process among clinical residents in Iran.We conducted a cross sectional survey during September to December 2012 at the teaching hospitals of Tehran University of Medical Sciences among 79 clinical residents from different medical specialties. A valid and reliable questionnaire consisted of five sections and 27 statements were used in this research. We applied Spearman and Mann Whitney test for correlation between variables. Findings showed that the knowledge of residents about EBM is low. Their attitude towards EBM was positive but their knowledge and skills in regard with the evidence based medical information resources were mostly limited to PubMed and Google scholar. The main barrier was the lack of enough time to practicing EBM. There was no significant correlation between residency grade and familiarity and use of electronic EBM resources (Spearman, P = 0.138). Integration of training approaches like journal clubs or workshops with clinical practice is suggested.

Keywords: evidence-based medicine, clinical residents, decision-making, attitude, questionnaire

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Authors: David J. Foran, Nhan Do, Samuel Ajjarapu, Wenjin Chen, Tahsin Kurc, Joel H. Saltz

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The large-scale data and computational requirements of investigators throughout the clinical and research communities demand an informatics infrastructure that supports both existing and new investigative and translational projects in a robust, secure environment. In some subspecialties of medicine and research, the capacity to generate data has outpaced the methods and technology used to aggregate, organize, access, and reliably retrieve this information. Leading health care centers now recognize the utility of establishing an enterprise-wide, clinical data warehouse. The primary benefits that can be realized through such efforts include cost savings, efficient tracking of outcomes, advanced clinical decision support, improved prognostic accuracy, and more reliable clinical trials matching. The overarching objective of the work presented here is the development and implementation of a flexible Intelligent Retrieval and Interrogation System (IRIS) that exploits the combined use of computational imaging, genomics, and data-mining capabilities to facilitate clinical assessments and translational research in oncology. The proposed System includes a multi-modal, Clinical & Research Data Warehouse (CRDW) that is tightly integrated with a suite of computational and machine-learning tools to provide insight into the underlying tumor characteristics that are not be apparent by human inspection alone. A key distinguishing feature of the System is a configurable Extract, Transform and Load (ETL) interface that enables it to adapt to different clinical and research data environments. This project is motivated by the growing emphasis on establishing Learning Health Systems in which cyclical hypothesis generation and evidence evaluation become integral to improving the quality of patient care. To facilitate iterative prototyping and optimization of the algorithms and workflows for the System, the team has already implemented a fully functional Warehouse that can reliably aggregate information originating from multiple data sources including EHR’s, Clinical Trial Management Systems, Tumor Registries, Biospecimen Repositories, Radiology PAC systems, Digital Pathology archives, Unstructured Clinical Documents, and Next Generation Sequencing services. The System enables physicians to systematically mine and review the molecular, genomic, image-based, and correlated clinical information about patient tumors individually or as part of large cohorts to identify patterns that may influence treatment decisions and outcomes. The CRDW core system has facilitated peer-reviewed publications and funded projects, including an NIH-sponsored collaboration to enhance the cancer registries in Georgia, Kentucky, New Jersey, and New York, with machine-learning based classifications and quantitative pathomics, feature sets. The CRDW has also resulted in a collaboration with the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) at the U.S. Department of Veterans Affairs to develop algorithms and workflows to automate the analysis of lung adenocarcinoma. Those studies showed that combining computational nuclear signatures with traditional WHO criteria through the use of deep convolutional neural networks (CNNs) led to improved discrimination among tumor growth patterns. The team has also leveraged the Warehouse to support studies to investigate the potential of utilizing a combination of genomic and computational imaging signatures to characterize prostate cancer. The results of those studies show that integrating image biomarkers with genomic pathway scores is more strongly correlated with disease recurrence than using standard clinical markers.

Keywords: clinical data warehouse, decision support, data-mining, intelligent databases, machine-learning.

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Authors: Maria Pratt, Lynn Martin

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Context: In nursing education, clinical instructors are crucial in assessing and evaluating students' performance in clinical courses. However, instructors often struggle when assigning failing grades to students at risk of failing. Research Aim: This qualitative study aims to understand clinical instructors' experiences evaluating students with unsatisfactory performance, including how reflection and collegial support impact this evaluation process. Methodology, Data Collection, and Analysis Procedures: This study employs Gadamer's Hermeneutic Inquiry as the research methodology. A purposive maximum variation sampling technique was used to recruit eight clinical instructors from a collaborative undergraduate nursing program in Southwestern Ontario. Semi-structured, open-ended, and audio-taped interviews were conducted with the participants. The hermeneutic analysis was applied to interpret the interview data to allow for a thorough exploration and interpretation of the instructors' experiences evaluating failing students. Findings: The main findings of this qualitative research indicate that evaluating failing students was emotionally draining for the clinical instructors who experienced multiple challenges, uncertainties, and negative feelings associated with assigning failing grades. However, the analysis revealed that ongoing reflection and collegial support played a crucial role in mitigating the challenges they experienced. Conclusion: This study contributes to the theoretical understanding of nursing education by shedding light on clinical instructors' challenges in evaluating failing students. It emphasizes the emotional toll associated with this process and the role that reflection and collegial support play in alleviating those challenges. The findings underscore the need for ongoing professional development and support for instructors in nursing education. By understanding and addressing clinical instructors' experiences, nursing education programs can better equip them to effectively evaluate struggling students and provide the necessary support for their professional growth.

Keywords: clinical instructor, student evaluation, nursing, reflection, support

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Authors: Joshua Midha

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This paper provides an evaluation of an intervention designed to promote a risk-realistic environment for women in the workplace and regulate their risk-related decision-making. In past research, women -specifically women of color- are highly risk-averse, and this may prove to be an innate obstacle in gender progress in corporations. By helping women see the risks and the benefits and increasing potential benefits, we can increase the chances of success in the workplace. Our intervention was a success and significantly increased comfort, trust, and frequency in the use of decision-making skills in the workplace. In this paper, we explore the intervention, the methods, the results, and the implications.

Keywords: behavioral economics, decision support, risk, gender equality

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Authors: Lei Chen, Jian Jiao, Tingdi Zhao

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Failures of automotive electric/electronic systems, which are universally considered to be safety-critical and software-intensive, may cause catastrophic accidents. Analysis and verification of failures in these kinds of systems is a big challenge with increasing system complexity. Model-checking is often employed to allow formal verification by ensuring that the system model conforms to specified safety properties. The system-level effects of failures are established, and the effects on system behavior are observed through the formal verification. A hazard analysis technique, called Systems-Theoretic Process Analysis, is capable of identifying design flaws which may cause potential failure hazardous, including software and system design errors and unsafe interactions among multiple system components. This paper provides a concept on how to use model-checking integrated with Systems-Theoretic Process Analysis to perform failure analysis and verification of automotive electric/electronic systems. As a result, safety requirements are optimized, and failure propagation paths are found. Finally, an automotive electric/electronic system case study is used to verify the effectiveness and practicability of the method.

Keywords: failure analysis and verification, model checking, system-theoretic process analysis, automotive electric/electronic system

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Authors: Klaus Peter Scherer, Daniel Knöll, Constantin Rieder

Abstract:

Problem and Purpose: Intelligent systems are available and helpful to support the human being decision process, especially when complex surgical eye interventions are necessary and must be performed. Normally, such a decision support system consists of a knowledge-based module, which is responsible for the real assistance power, given by an explanation and logical reasoning processes. The interview based acquisition and generation of the complex knowledge itself is very crucial, because there are different correlations between the complex parameters. So, in this project (semi)automated self-learning methods are researched and developed for an enhancement of the quality of such a decision support system. Methods: For ophthalmic data sets of real patients in a hospital, advanced data mining procedures seem to be very helpful. Especially subgroup analysis methods are developed, extended and used to analyze and find out the correlations and conditional dependencies between the structured patient data. After finding causal dependencies, a ranking must be performed for the generation of rule-based representations. For this, anonymous patient data are transformed into a special machine language format. The imported data are used as input for algorithms of conditioned probability methods to calculate the parameter distributions concerning a special given goal parameter. Results: In the field of knowledge discovery advanced methods and applications could be performed to produce operation and patient related correlations. So, new knowledge was generated by finding causal relations between the operational equipment, the medical instances and patient specific history by a dependency ranking process. After transformation in association rules logically based representations were available for the clinical experts to evaluate the new knowledge. The structured data sets take account of about 80 parameters as special characteristic features per patient. For different extended patient groups (100, 300, 500), as well one target value as well multi-target values were set for the subgroup analysis. So the newly generated hypotheses could be interpreted regarding the dependency or independency of patient number. Conclusions: The aim and the advantage of such a semi-automatically self-learning process are the extensions of the knowledge base by finding new parameter correlations. The discovered knowledge is transformed into association rules and serves as rule-based representation of the knowledge in the knowledge base. Even more, than one goal parameter of interest can be considered by the semi-automated learning process. With ranking procedures, the most strong premises and also conjunctive associated conditions can be found to conclude the interested goal parameter. So the knowledge, hidden in structured tables or lists can be extracted as rule-based representation. This is a real assistance power for the communication with the clinical experts.

Keywords: an expert system, knowledge-based support, ophthalmic decision support, self-learning methods

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Authors: Omar Mayyas

Abstract:

Clinical decision-making (CDM) is essential to community health nursing (CHN) education. For this reason, nursing educators are responsible for developing these skills among nursing students because nursing students are exposed to highly critical conditions after graduation. However, due to limited exposure to real-world situations, many nursing students need help developing clinical decision-making skills in this area. Therefore, the impact of Virtual Simulation (VS) on community health nursing students' clinical decision-making in nursing education has to be investigated. This study aims to examine the difference in CDM ability among CHN students who received traditional education compared to those who received VS classes, to identify the factors that may influence CDM ability differences between CHN students who received a traditional education and VS classes, and to provide recommendations for educational programs that can enhance the CDM ability of CHN students and improve the quality of care provided in community settings. A mixed-method study will conduct. A randomized controlled trial will compare the CDM ability of CHN students who received 1hr traditional class with another group who received 1hr VS scenario about diabetic patient nursing care. Sixty-four students in each group will randomly select to be exposed to the intervention from undergraduate nursing students who completed the CHN course at York University. The participants will receive the same Clinical Decision Making in Nursing Scale (CDMNS) questionnaire. The study intervention will follow the Medical Research Council (MRC) approach. SPSS and content analysis will use for data analysis.

Keywords: clinical decision-making, virtual simulation, community health nursing students, community health nursing education

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