Search results for: clinical decision support systems

Authors: P. Ghann, J. Shiguang, C. Zhou

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Access control is one of the most challenging issues facing information security. Access control is defined as, the ability to permit or deny access to a particular computational resource or digital information by an unauthorized user or subject. The concept of usage control (UCON) has been introduced as a unified approach to capture a number of extensions for access control models and systems. In UCON, an access decision is determined by three factors: Authorizations, obligations and conditions. Attribute mutability and decision continuity are two distinct characteristics introduced by UCON for the first time. An observation of UCON components indicates that, the components are predefined and static. In this paper, we propose a new and flexible model of usage control for the creation and elimination of some of these components; for example new objects, subjects, attributes and integrate these with the original UCON model. We also propose a model for concurrent usage scenarios in UCON.

Keywords: access control, concurrency, digital container, usage control

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Authors: Ana Neves, John Leander, Ignacio Gonzalez, Raid Karoumi

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Systematic monitoring and inspection are needed to assess the present state of a structure and predict its future condition. If an irregularity is noticed, repair actions may take place and the adequate intervention will most probably reduce the future costs with maintenance, minimize downtime and increase safety by avoiding the failure of the structure as a whole or of one of its structural parts. For this to be possible decisions must be made at the right time, which implies using systems that can detect abnormalities in their early stage. In this sense, Structural Health Monitoring (SHM) is seen as an effective tool for improving the safety and reliability of infrastructures. This paper explores the decision-making problem in SHM regarding the maintenance of civil engineering structures. The aim is to assess the present condition of a bridge based exclusively on measurements using the suggested method in this paper, such that action is taken coherently with the information made available by the monitoring system. Artificial Neural Networks are trained and their ability to predict structural behavior is evaluated in the light of a case study where acceleration measurements are acquired from a bridge located in Stockholm, Sweden. This relatively old bridge is presently still in operation despite experiencing obvious problems already reported in previous inspections. The prediction errors provide a measure of the accuracy of the algorithm and are subjected to further investigation, which comprises concepts like clustering analysis and statistical hypothesis testing. These enable to interpret the obtained prediction errors, draw conclusions about the state of the structure and thus support decision making regarding its maintenance.

Keywords: artificial neural networks, clustering analysis, model-free damage detection, statistical hypothesis testing, structural health monitoring

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Authors: Zainab Mutlaq Ibrahim, Mohamed Bader-El-Den, Mihaela Cocea

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Students' textual feedback can hold unique patterns and useful information about learning process, it can hold information about advantages and disadvantages of teaching methods, assessment components, facilities, and other aspects of teaching. The results of analysing such a feedback can form a key point for institutions’ decision makers to advance and update their systems accordingly. This paper proposes a data mining framework for analysing end of unit general textual feedback using part of speech feature (PoS) with four machine learning algorithms: support vector machines, decision tree, random forest, and naive bays. The proposed framework has two tasks: first, to use the above algorithms to build an optimal model that automatically classifies the whole data set into two subsets, one subset is tailored to assessment practices (assessment related), and the other one is the non-assessment related data. Second task to use the same algorithms to build an optimal model for whole data set, and the new data subsets to automatically detect their sentiment. The significance of this paper is to compare the performance of the above four algorithms using part of speech feature to the performance of the same algorithms using n-grams feature. The paper follows Knowledge Discovery and Data Mining (KDDM) framework to construct the classification and sentiment analysis models, which is understanding the assessment domain, cleaning and pre-processing the data set, selecting and running the data mining algorithm, interpreting mined patterns, and consolidating the discovered knowledge. The results of this paper experiments show that both models which used both features performed very well regarding first task. But regarding the second task, models that used part of speech feature has underperformed in comparison with models that used unigrams and bigrams.

Keywords: assessment, part of speech, sentiment analysis, student feedback

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Authors: Tabinda Sadiq, Tehmina Ashfaq Qazi, Hoor Shumail

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Recently, the advent of emerging technology has created an emerging generation of restaurant marketing. It explores the aspects that influence customers’ decision-making process in selecting a restaurant after reading food bloggers' reviews online. The motivation behind this research is to investigate the correlation between the credibility of the source and their attitude toward restaurant visits. The researcher collected the data by distributing a survey questionnaire through google forms by employing the Source credibility theory. Non- probability purposive sampling technique was used to collect data. The questionnaire used a predeveloped and validated scale by Ohanian to measure the relationship. Also, the researcher collected data from 250 respondents in order to investigate the influence of food bloggers on Gen Z's decision-making process. SPSS statistical version 26 was used for statistical testing and analyzing the data. The findings of the survey revealed that there is a moderate positive correlation between the variables. So, it can be analyzed that food bloggers do have an impact on Generation Z's decision making process.

Keywords: credibility, decision making, food bloggers, generation z, e-wom

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Authors: Diana Vieira Figueiredo, Rita Ramos Miguel, Maria do Céu Salvador, Luiza Nobre-Lima, Daniel RIjo, Paula Vagos

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Social Anxiety Disorder (SAD) is characterized by a marked and persistent fear of social and/or performance situations in which one may be exposed to the scrutiny of others.  SAD has its usual onset and is highly prevalent during adolescence; if left untreated, it often has a chronic and unremitting course. So, it seems important to understand the psychological processes that might predict the development of SAD. One of these processes may be self-compassion, which has been found to be associated with social anxiety in both adults and adolescents. Self-compassion involves three main components, each with a positive (compassionate behavior) and negative (uncompassionate behavior) pole – self-kindness versus self-judgment, common humanity versus isolation, and mindfulness versus over-identification. The negative indicators of self-compassion (self-judgement, isolation, and over-identification) were found to be more strongly linked to mental health problems than the positive indicators (self-kindness, common humanity, and mindfulness). Additionally, negative associations were found between the positive indicators of self-compassion (self-kindness, common humanity, mindfulness) and psychopathology. The current study aimed to investigate the role of self-kindness, self-judgment, common humanity, isolation, mindfulness, and over-identification in the likelihood of an adolescent presenting SAD by comparing groups of normative and socially anxious adolescents. The sample consisted of 32 adolescents (Mage = 15.88, SD = .833) of which 23 were girls. Adolescents were assessed through a clinical structured interview that led 17 to be assigned to the clinical group (presenting a primary diagnosis of SAD) and 15 to be assigned to the non-clinical group (presenting no clinical diagnosis). Variables under study were measured through the Self-Compassion Scale for adolescents (SCS-A), which assesses the six indicators of self-compassion presented above. Six separate models were tested, each with one of the subscales of the SCS-A as the independent variable and with the group (clinical versus non-clinical) as the dependent variable. The models considering isolation, over-identification, self-judgement, and self-kindness fitted the data and accurately predicted group belonging for between 75% to 84.4% of cases. Results indicated that the log of the odds of an adolescent presenting SAD was positively related to isolation, over-identification, and self-judgement and negatively associated with self-kindness. Findings provide support for the idea that decreased self-compassion may place adolescents at increased risk for experiencing clinical levels of social anxiety: on the one hand, adolescents with higher levels of isolation, over-identification, and self-judgement seem to be more prone to the development of psychopathological levels of social anxiety; on the other hand, self-kindness may play a protective role in the development of SAD in this developmental phase. So, if focusing on social feared consequences and perceiving to be different from others may be distinctive features of SAD, developing self-kindness may be the antidote to promote diminished levels of social anxiety and more.

Keywords: adolescents, social anxiety disorder, self-compassion, diagnosis odds-ration

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Authors: Hossein Ghaedamini, Salman Farahbakhsh, Alireza Amirbeigi, Zahra Saghafi, Salman Daneshi, Alireza Ghaedamini

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Background: Assessing the challenges of clinical education of medical students is one of the most important and sensitive parts of medical education. The aim of this study was to investigate the views and experiences of Kerman medical students on the factors that facilitate and inhibit the quality of clinical education. Materials and Methods: This research was qualitative and used a phenomenological approach. The study population included medical interns of Kerman University of Medical Sciences in 1400. The method of data collection was in-depth interviews with participants. Data were encoded and analyzed by Claizey stepwise model. Results: First, about 540 primary codes were extracted in the form of two main themes (facilitators and inhibitors) and 10 sub-themes including providing motivational models and creating interest in interns, high scientific level of professors and the appropriate quality of their teaching, the use of technology in the clinical education process, delegating authority and freedom of action and more responsibilities to interns, inappropriate treatment of some officials, professors, assistants and department staff with their interns, inadequate educational programming, lack of necessary cooperation and providing inappropriate treatment by clinical training experts for interns, inadequate evaluation method in clinical training for interns, poor quality mornings, the unefficiency of grand rounds, the inappropriate way of evaluating clinical training for interns, the lack of suitable facilities and conditions with the position of a medical intern, and the hardwork of some departments were categorized. Conclusion: Clinical education is always mixed with special principles and subtleties, and special attention to facilitators and inhibitors in this process has an important role in improving its quality.

Keywords: clinical education, medical students, qualitative study, education

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Authors: Lu-Chiu Huang, Pei-Pei Chen, Li-Chin Yu, Chiao-Wen Kuo, Tsui-Tao Liu, Rung-Chuang Feng

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Purpose: People put increasing emphasis on demands of medical quality and protecting their interests. Patients' or family's dissatisfaction with medical care may easily lead to medical dispute. Physician-family communication plays an essential role in medical care. A sound communication cannot only strengthen patients' belief in the medical team but make patient have definite insight into treatment course of the disease. A family meeting provides an effective platform for communication between clinical staff, patients and family. Decisions and consensuses formed in family meetings can promote patients' or family's satisfaction with medical care. Clinical staff's attitudes toward family meeting may determine behavioral intentions to hold family meeting. This study aims to explore clinical staff's difficulties in holding family meeting and evaluate how their attitudes and behavior influence the effect of family meetings. Methods: This was a cross-sectional study. It was conducted at a regional teaching hospital in Taipei city. The research team developed its own structural questionnaires, whose expert validity was checked by the nursing experts. Participants filled in the questionnaires online. Data were collected by convenience sampling. A total of 568 participants were invited. They included doctors, nurses, social workers, and so on. Results: 1) The average score of ‘clinical staff’s attitudes to family meetings’ was 5.15 (SD=0.898). It fell between ‘somewhat agree’ and ‘mostly agree’ on the 7-point likert scale. It indicated that clinical staff had positive attitudes toward family meetings, 2) The average score of ‘clinical staff’s behavior to family meetings’ was 5.61 (SD=0.937). It fell between ‘somewhat agree’ and ‘mostly agree’ on the 7-point likert scale. It meant clinical staff tended to have positive behavior at the family meeting, and 3) The average score of ‘Difficulty in conducting family meetings’ was 5.15 (SD=0.897). It fell between ‘somewhat agree’ and ‘mostly agree’ on the 7-point likert scale. The higher the score was, the less difficulty the clinical staff felt. It demonstrated clinical staff felt less difficulty in conducting family meetings. Clinical staff's identification with family meetings brought favored effects. Persistent and active promotion for family meetings can bring patients and family more benefits. Implications for practice: Understanding clinical staff's difficulty in participating family meeting and exploring their attitudes or behavior toward physician-family communication are helpful to develop modes of interaction. Consequently, quality and satisfaction of physician-family communication can be increased.

Keywords: clinical staff, communication, family meeting, physician-family

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Authors: Phawida Wattanasoonthorn

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Ventilator-associated pneumonia is a serious infection found to be among the top three infections in the hospital. To investigate the effects of clinical practice guideline on knowledge and preventive practices of nursing personnel, and incidences of ventilator-associated pneumonia. A pre-post quasi-experimental study on 17 professional nurses, and 123 ventilator-associated pneumonia patients admitted to the surgical intensive care unit, and the accident and surgical ward of Songkhla Hospital from October 2013 to January 2014. The study found that after using the clinical practice guideline, the subjects’ median score increased from 16.00 to 19.00. The increase in practicing correctly was from 66.01 percent to 79.03 percent with the statistical significance level of .05, and the incidences of ventilator-associated pneumonia decreased by 5.00 percent. The results of this study revealed that the use of the clinical practice guideline helped increase knowledge and practice skill of nursing personnel, and decrease incidences of ventilator-associated pneumonia. Thus, nursing personnel should be encouraged, reminded and promoted to continue using the practice guideline through various means including training, providing knowledge, giving feedback, and putting up posters to remind them of practicing correctly and sustainably.

Keywords: Clinical Practice Guideline, knowledge, Preventive Ventilator, Pneumonia

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Authors: Hongxia Wang, Yanjie Wang, Xiuqin Wang, Linlin Mo, Shuangshuang Niu

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Special Education Resource Center (SERC) is the localized product in the development of inclusive education in People’s Republic of China, which provides professional support and service for the students with special education needs(SEN) and their parents, teachers as well as inclusive schools. The study investigated 155 administrators, resource teachers and inclusive education teachers from primary and secondary schools in Beijing. The results indicate that: (1) The surveyed teachers put highest expectation of SERC on specialized guidance and teacher training , instead of research and administration function; (2) Each dimension of professional support needs gets higher scores, in which individual guidance gets highest score, followed by instruction guidance, psychological counseling, proposing suggestions, informational support and teacher training; (3) locality and training experience of surveyed teachers significantly influence their expectations and support needs of SERC.

Keywords: special education resource center (SERC) , functional expectation, professional support needs, support system

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Authors: Mehrnaz Mostafavi

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The assessment and categorization of incidental lung nodules present a considerable challenge in healthcare, often necessitating resource-intensive multiple computed tomography (CT) scans for growth confirmation. This research addresses this issue by introducing a distinct computational approach leveraging radiomics and deep-learning methods. However, understanding local services is essential before implementing these advancements. With diverse tracking methods in place, there is a need for efficient and accurate identification approaches, especially in the context of managing lung nodules alongside pre-existing cancer scenarios. This study explores the integration of text-based algorithms in medical data curation, indicating their efficacy in conjunction with machine learning and deep-learning models for identifying lung nodules. Combining medical images with text data has demonstrated superior data retrieval compared to using each modality independently. While deep learning and text analysis show potential in detecting previously missed nodules, challenges persist, such as increased false positives. The presented research introduces a Structured-Query-Language (SQL) algorithm designed for identifying pulmonary nodules in a tertiary cancer center, externally validated at another hospital. Leveraging natural language processing (NLP) and machine learning, the algorithm categorizes lung nodule reports based on sentence features, aiming to facilitate research and assess clinical pathways. The hypothesis posits that the algorithm can accurately identify lung nodule CT scans and predict concerning nodule features using machine-learning classifiers. Through a retrospective observational study spanning a decade, CT scan reports were collected, and an algorithm was developed to extract and classify data. Results underscore the complexity of lung nodule cohorts in cancer centers, emphasizing the importance of careful evaluation before assuming a metastatic origin. The SQL and NLP algorithms demonstrated high accuracy in identifying lung nodule sentences, indicating potential for local service evaluation and research dataset creation. Machine-learning models exhibited strong accuracy in predicting concerning changes in lung nodule scan reports. While limitations include variability in disease group attribution, the potential for correlation rather than causality in clinical findings, and the need for further external validation, the algorithm's accuracy and potential to support clinical decision-making and healthcare automation represent a significant stride in lung nodule management and research.

Keywords: lung cancer diagnosis, structured-query-language (SQL), natural language processing (NLP), machine learning, CT scans

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Authors: Ali Zaimi

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Citizen participation in local government is an opportunity given to citizens and government to increase communication between them, create public support for local government plans and most important grow public trust in government. Also, the citizens’ involvement in the political process is an important part of democracy. This study aims to define the strategies for increasing citizen participation in local governance and concentrated in two important mechanisms such as participatory budget and public policy councils. Three strategies that promote more effective citizen involvement in local governance are understanding and using formal institutions of power, collaboration of citizens’ groups and governments officials to jointly formulate programs plans, electing and appointing local officials. A unique aspect of citizen participation to operate effectively is the transparency of government and the inclusion of actors into decision-making. The citizen engagement in local governance enhances accountability and problem solving, promote more inclusive and cohesive communities and enlarge the quality and quantity of initiatives made by communities.

Keywords: accountability, citizen participation, democracy, government

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Authors: Akriti Kafle Baral, Ruixing Zhang, Dzifa K Lalit, Manthar M Alli

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Introduction: Hemodialysis is the most common type of dialysis globally approximately million are reported to receive this type of dialysis. Psychosocial issues in hemodialysis are the psychological and socioeconomic burdens emanating from the initiation and course of treatment and have the potential for gross deterioration in the quality of life and general well-being of patients. Understanding the psychosocial issues and needs of patients undergoing hemodialysis could pave the way for comprehensive support and therapies designed to reduce stress, improve social support, and foster mental resilience. Objectives: The aim of this study was to explore the psychosocial issues and support needs of patients undergoing hemodialysis at a tertiary care center in Nepal. Methods: A qualitative descriptive study was conducted among 20 purposefully selected patients attending hemodialysis treatment at Pokhara Academy of Health Sciences, Nepal. Data was analyzed via thematic analysis. Results: The study resulted in three major themes which included Emotional, psychological, and spiritual struggles, Social and economic impacts, and Support and information needs. Moreover, 16 sub-themes emerged which are Frustration with daily life, Constant fear of death, Thoughts of self-harm, Perceived Burden on Family, Sense of Divine Punishment, Sense of Unfairness, Fear about future uncertainties, Social avoidance, Social stigmatization, Loss of employment, Financial strain, Transportation challenges, Need for early, clear and comprehensive information, Need for support and reassurance from family, Support through peer connections, and Reassurance from healthcare providers. Conclusion: The findings of this study indicate that patients undergoing hemodialysis in Nepal experience numerous hardships and multifaceted struggles that require support from different dimensions. Establishing robust support systems that include family involvement, peer networks, and effective communication from healthcare professionals can significantly mitigate feelings of anxiety and isolation.

Keywords: hemodialysis, psychosocial issues, support needs, chronic kidney disease, end stage renal disease, Nepal

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Authors: Gulnara N. Nabiyeva, Stephen M. Wheeler

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Geographic Information Systems (GIS) is a multipurpose computer-based tool that provides a sophisticated ability to map and analyze data on different spatial layers. However, GIS is far more easily applied in some policy areas than others. This paper seeks to determine the areas of sustainable development, including environmental, economic, and social dimensions, where GIS has been used to date to support efforts to implement the United Nations Sustainable Development Goals (SDGs), and to discuss potential areas where it might be used more. Based on an extensive analysis of published literature, we ranked the SDGs according to how frequently GIS has been used to study related policy. We found that SDG#15 “Life on Land” is most often addressed with GIS, following by SDG#11 “Sustainable Cities and Communities”, and SDG#13 “Climate Action”. On the other hand, we determined that SDG#2 “Zero Hunger”, SDG#8 “Decent Work and Economic Growth”, and SDG#16 “Peace, Justice, and Strong Institutions” are least addressed with GIS. The paper outlines some specific ways that GIS might be applied to the SDGs least linked to this tool currently.

Keywords: GIS, GIS application, sustainable community development, sustainable development goals

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Authors: Magri Hicham, Noreddine Abghour, Mohamed Ouzzif

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The 5th generation of mobile networks is term used in various research papers and projects to identify the next major phase of mobile telecommunications standards. 5G wireless networks will support higher peak data rate, lower latency and provide best connections with QoS guarenty. In this article, we discuss various promising technologies for 5G wireless communication systems, such as IPv6 support, World Wide Wireless Web (WWWW), Dynamic Adhoc Wireless Networks (DAWN), BEAM DIVISION MULTIPLE ACCESS (BDMA), Cloud Computing and cognitive radio technology.

Keywords: WWWW, BDMA, DAWN, 5G, 4G, IPv6, Cloud Computing

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Authors: Merav Ben Natan, Moran Makhoul Khuri, Haviel Hammer, Maya Yarkoni

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Background: Studies indicate that nursing students often rank hospice nursing among their least preferred career paths. Understanding factors influencing their intent to work in hospice care is essential for improving interest in this field. Aim: This study aimed to explore the relationship between nursing students' intention to pursue a career in hospice care and various factors, including their attitudes towards caring for dying patients, death anxiety, personal or professional experience with dying patients, and the type of nursing program they are enrolled in. Methods: In this cross-sectional study, 200 nursing students completed an online survey using the Frommelt Attitude Toward Care of the Dying Scale and the Turkish Death Anxiety Scale. The survey assessed students' intentions to work in hospice care and related variables. Results: Only 11% of participants expressed an interest in working in hospice care. Students in the accelerated program for non-nursing Bachelor of Arts graduates showed a higher intention to work in hospice care compared to those in the generic program (β = 0.27, P < .001). Conversely, completion of clinical experience in a medical ward was associated with a lower intention to work in hospice care (β = −0.21, P < .01). Conclusions: The findings suggest that nursing students in accelerated programs for non-nursing graduates are more likely to intend to work in hospice care. Enhanced experience and support are recommended to sustain their interest. Clinical experience in medical wards does not effectively substitute for hospice-specific clinical experience.

Keywords: hospice nursing, nursing students, death anxiety, career intentions

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Authors: A. Luft, S. Bremen, N. Balc

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The task of flexibility planning and design, just like factory planning, for example, is to create the long-term systemic framework that constitutes the restriction for short-term operational management. This is a strategic challenge since, due to the decision defect character of the underlying flexibility problem, multiple types of flexibility need to be considered over the course of various scenarios, production programs, and production system configurations. In this context, an evaluation model has been developed that integrates both conventional and additive resources on a basic task level and allows the quantification of flexibility enhancement in terms of mix and volume flexibility, complexity reduction, and machine capacity. The model helps companies to decide in early decision-making processes about the potential gains of implementing additive manufacturing technologies on a strategic level. For companies, it is essential to consider both additive and conventional manufacturing beyond pure unit costs. It is necessary to achieve an integrative view of manufacturing that incorporates both additive and conventional manufacturing resources and quantifies their potential with regard to flexibility and manufacturing complexity. This also requires a structured process for the strategic production systems design that spans the design of various scenarios and allows for multi-dimensional and comparative analysis. A respective guideline for the planning of additive resources on a strategic level is being laid out in this paper.

Keywords: additive manufacturing, production system design, flexibility enhancement, strategic guideline

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Authors: Kim Michelle Siegling, Thomas Spengler, Sebastian Herzog

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In personnel economics, the choice of a leadership style is about the question of how a supervisor should lead his or her employees in such a way that operational goals are achieved. In this paper, it is assumed that such leadership decisions are made according to the situation. Thus, the optimal or at least a permissible leadership style has to be selected from a set of several possible leadership styles. For this choice, a wide range of models has been developed in the scientific literature, from which the so-called normative decision model will be picked out and focused on. While the original model is based on univocal rules, this paper develops a fuzzy rule system.

Keywords: leadership, leadership styles, rule based systems, fuzzy logic

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Authors: Margaret S. Wright

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Background/Significance: During many recent public health emergencies/disasters, public health nursing data has been missing or delayed, potentially impacting the decision-making and response. Data used as evidence for decision-making in response, planning, and mitigation has been erratic and slow, decreasing the ability to respond. Methodology: Applying best practices in data management and data use in public health settings, and guided by the concepts outlined in ‘Disaster Standards of Care’ models leads to the development of recommendations for a model of best practices in data management and use in public health disasters/emergencies by public health nurses. As the ‘patient’ in public health disasters/emergencies is the community (local, regional or national), guidelines for patient documentation are incorporated in the recommendations. Findings: Using model public health nurses could better plan how to prepare for, respond to, and mitigate disasters in their communities, and better participate in decision-making in all three phases bringing public health nursing data to the discussion as part of the evidence base for decision-making.

Keywords: data management, decision making, disaster planning documentation, public health nursing

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Authors: Wid Kattan, Rahaf Albarraq

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Background: Tokophobia is a pathological fear of pregnancy that can lead to the avoidance of childbirth. It is classified as primary or secondary. This report describes a patient with tokophobia, as well as her presentation, risk factors, comorbidities, and treatment. Case Presentation: A 43-year-old Saudi woman experienced tokophobia upon becoming pregnant for the fifth time. She was assessed in two clinical interviews by a consultant psychiatrist specializing in women’s mental health. In addition, she completed several questionnaires for assessment of different aspects of her mental health: overall depression, perinatal depression, generalized anxiety, maternal functioning, and fear of childbirth (FOC). Several risk factors and comorbidities that may have contributed to the development of tokophobia in this patient were discussed, including traumatic experiences in previous deliveries, the unplanned nature of the pregnancy, perinatal depression, and pronounced symptoms of anxiety. A collaborative decision to perform a C-section was made, in line with obstetric guidelines and good mental health practice. Full symptomatic recovery was achieved immediately after delivery. Conclusions: We hope to increase clinical awareness of the assessment and management of tokophobia, which is a relatively new concept and, as yet, understudied.

Keywords: tokophobia, fear of childbirth, mental health, anxiety, case report, depression, fear of delivery, psychiatry, cesarean section, perinatal depression

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Authors: J. Trarbach, S. Schosser, B. Vogt

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Decision-makers tend to prefer the first alternative over subsequent alternatives which is called the primacy effect. To reliably measure this effect, we conducted an experiment with real consequences for preference statements. Therefore, we elicit preferences of subjects using a rating scale, i.e. hypothetical preferences, and willingness to pay, i.e. real preferences, for two sequences of pain. Within these sequences, both overall intensity and duration of pain are identical. Hence, a rational decision-maker should be indifferent, whereas the primacy effect predicts a stronger preference for the first sequence. What we see is a primacy effect only for hypothetical preferences. This effect vanishes for real preferences.

Keywords: decision making, primacy effect, real incentives, willingness to pay

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Authors: Shang-Yu Chiang, Yu-Shan Tsai, Shih-Hsien Sung, Chung-Ming Lo

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Mitral regurgitation (MR) is a heart disorder which the mitral valve does not close properly when the heart pumps out blood. MR is the most common form of valvular heart disease in the adult population. The diagnostic echocardiographic finding of MR is straightforward due to the well-known clinical evidence. In the determination of MR severity, quantification of sonographic findings would be useful for clinical decision making. Clinically, the vena contracta is a standard for MR evaluation. Vena contracta is the point in a blood stream where the diameter of the stream is the least, and the velocity is the maximum. The quantification of vena contracta, i.e. the vena contracta width (VCW) at mitral valve, can be a numeric measurement for severity assessment. However, manually delineating the VCW may not accurate enough. The result highly depends on the operator experience. Therefore, this study proposed an automatic method to quantify VCW to evaluate MR severity. Based on color Doppler ultrasound, VCW can be observed from the blood flows to the probe as the appearance of red or yellow area. The corresponding brightness represents the value of the flow rate. In the experiment, colors were firstly transformed into HSV (hue, saturation and value) to be closely align with the way human vision perceives red and yellow. Using ellipse to fit the high flow rate area in left atrium, the angle between the mitral valve and the ultrasound probe was calculated to get the vertical shortest diameter as the VCW. Taking the manual measurement as the standard, the method achieved only 0.02 (0.38 vs. 0.36) to 0.03 (0.42 vs. 0.45) cm differences. The result showed that the proposed automatic VCW extraction can be efficient and accurate for clinical use. The process also has the potential to reduce intra- or inter-observer variability at measuring subtle distances.

Keywords: mitral regurgitation, vena contracta, color doppler, image processing

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Authors: Lavanya Madhuri Bollipo, K. V. Kadambari

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Objective: To discuss key issues in the diagnosis of Parkinson disease (PD), To discuss features influencing PD progression, To discuss importance of brain SPECT data in PD diagnosis, and To discuss the essentiality of machine learning techniques in early diagnosis of PD. An accurate and early diagnosis of PD is nowadays a challenge as clinical symptoms in PD arise only when there is more than 60% loss of dopaminergic neurons. So far there are no laboratory tests for the diagnosis of PD, causing a high rate of misdiagnosis especially when the disease is in the early stages. Recent neuroimaging studies with brain SPECT using 123I-Ioflupane (DaTSCAN) as radiotracer shown to be widely used to assist the diagnosis of PD even in its early stages. Machine learning techniques can be used in combination with image analysis procedures to develop computer-aided diagnosis (CAD) systems for PD. This paper addressed recent studies involving diagnosis of PD in its early stages using brain SPECT data with Machine Learning Techniques.

Keywords: Parkinson disease (PD), dopamine transporter, single-photon emission computed tomography (SPECT), support vector machine (SVM)

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Authors: Ofra Walter Btel Liran Hazan

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This study’s goal was to clarify whether psychological capital (PsyCap) mediated the relations between social support and subjective well-being among post-secondary students during the Covid-19 pandemic and to assess whether students diagnosed with a learning disability (LD) and/or attention deficit hyperactivity disorder (ADHD) differed from others in their reliance on social support and their level of PsyCap and subjective wellbeing. Participants were257 students, 152 diagnosed with LD/ADHD and the rest neurotypical. The study used four questionnaires: demographic and academic information; Psychological Capital Questionnaire (PCQ); Subjective Well-Being Index; social support questionnaire. The results indicated PsyCapmediated relations between social support and subjective wellbeing. Students diagnosed with LD/ADHD differed from neurotypicals in their PsyCap and subjective wellbeing levels but not in their social support. In addition, the relations between PsyCap and social support were stronger among students diagnosed with LD/ADHD. PsyCap was an important resource for all participants and was related to social support and subjective wellbeing, making it especially valuable for LD/ADHD students facing new and threatening situations, such as the Covid-19 pandemic.

Keywords: LD/ADHD post-secondary students, subjective wellbeing, social support, PsyCap, covid-19

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Authors: Zahra Hamedani

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Many wonderful technological developments in recent years has opened up the possibility of using intelligent buildings for a number of important applications, ranging from minimizing resource usage as well as increasing building efficiency to maximizing comfort, adaption to inhabitants and responsiveness to environmental changes. The concept of an intelligent building refers to the highly embedded, interactive environment within which by exploiting the use of artificial intelligence provides the ability to know its configuration, anticipate the optimum dynamic response to prevailing environmental stimuli, and actuate the appropriate physical reaction to provide comfort and efficiency. This paper contains a general identification of the intelligence paradigm and its impacts on the architecture arena, that with examining the performance of artificial intelligence, a mechanism to analyze and finally for decision-making to control the environment will be described. This mechanism would be a hierarchy of the rational agents which includes decision-making, information, communication and physical layers. This multi-agent system relies upon machine learning techniques for automated discovery, prediction and decision-making. Then, the application of this mechanism regarding adaptation and responsiveness of intelligent building will be provided in two scales of environmental and user. Finally, we review the identifications of sustainability and evaluate the potentials of intelligent building systems in the creation of sustainable architecture and environment.

Keywords: artificial intelligence, intelligent building, responsiveness, adaption, sustainability

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Authors: Liane J. Ioannou, Jonathan Serpell, Joanne Dean, Cino Bendinelli, Jenny Gough, Dean Lisewski, Julie Miller, Win Meyer-Rochow, Stan Sidhu, Duncan Topliss, David Walters, John Zalcberg, Susannah Ahern

Abstract:

Background: The occurrence of thyroid cancer is increasing throughout the developed world, including Australia and New Zealand, and since the 1990s has become the fastest increasing malignancy. Following the success of a number of institutional databases that monitor outcomes after thyroid surgery, the Australian and New Zealand Endocrine Surgeons (ANZES) agreed to auspice the development of a bi-national thyroid cancer registry. Objectives: To establish a bi-national population-based clinical quality registry with the aim of monitoring and improving the quality of care provided to patients diagnosed with thyroid cancer in Australia and New Zealand. Patients and Methods: The Australian and New Zealand Thyroid Cancer Registry (ANZTCR) captures clinical data for all patients, over the age of 18 years, diagnosed with thyroid cancer, confirmed by histopathology report, that have been diagnosed, assessed or treated at a contributing hospital. Data is collected by endocrine surgeons using a web-based interface, REDCap, primarily via direct data entry. Results: A multi-disciplinary Steering Committee was formed, and with operational support from Monash University the ANZTCR was established in early 2017. The pilot phase of the registry is currently operating in Victoria, New South Wales, Queensland, Western Australia and South Australia, with over 30 sites expected to come on board across Australia and New Zealand in 2018. A modified-Delphi process was undertaken to determine the key quality indicators to be reported by the registry, and a minimum dataset was developed comprising information regarding thyroid cancer diagnosis, pathology, surgery, and 30-day follow up. Conclusion: There are very few established thyroid cancer registries internationally, yet clinical quality registries have shown valuable outcomes and patient benefits in other cancers. The establishment of the ANZTCR provides the opportunity for Australia and New Zealand to further understand the current practice in the treatment of thyroid cancer and reasons for variation in outcomes. The engagement of endocrine surgeons in supporting this initiative is crucial. While the pilot registry has a focus on early clinical outcomes, it is anticipated that future collection of longer-term outcome data particularly for patients with the poor prognostic disease will add significant further value to the registry.

Keywords: thyroid cancer, clinical registry, population health, quality improvement

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Authors: Getachew Belay Kassahun

Abstract:

Background: Locally established clinical laboratory reference intervals (RIs) are required to interpret laboratory test results for screening, diagnosis, and prognosis. The objective of this study was to establish a reference interval of clinical chemistry parameters among apparently healthy adolescents aged between 12 and 17 years in Mekelle, Tigrai, in the northern part of Ethiopia. Methods: Community-based cross-sectional study was employed from December 2018 to March 2019 in Mekelle City among 172 males and 172 females based on a Multi-stage sampling technique. Blood samples were tested for Fasting blood sugar (FBS), alanine amino transferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), Creatinine, urea, total protein, albumin (ALB), direct and indirect bilirubin (BIL.D and BIL.T) using 25 Bio system clinical chemistry analyzer. Results were analyzed using SPSS version 23 software and based on the Clinical Laboratory Standard Institute (CLSI)/ International Federation of Clinical Chemistry (IFCC) C 28-A3 Guideline which defines the reference interval as the 95% central range of 2.5th and 97.5th percentiles. Mann Whitney U test, descriptive statistics and box and whisker were statistical tools used for analysis. Results: This study observed statistically significant differences between males and females in ALP, ALT, AST, Urea and Creatinine Reference intervals. The established reference intervals for males and females, respectively, were: ALP (U/L) 79.48-492.12 versus 63.56-253.34, ALT (U/L) 4.54-23.69 versus 5.1-20.03, AST 15.7- 39.1 versus 13.3- 28.5, Urea (mg/dL) 9.33-24.99 versus 7.43-23.11, and Creatinine (mg/dL) 0.393-0.957 versus 0.301-0.846. The combined RIs for Total Protein (g/dL) were 6.08-7.85, ALB (g/dL) 4.42-5.46, FBS(mg/dL) 65-110, BIL.D (mg/dL) 0.033-0.532, and BIL.T (mg/dL) 0.106-0.812. Conclusions: The result showed a marked difference between sex and company-derived values for selected clinical chemistry parameters. Thus, the use of age and sex-specific locally established reference intervals for clinical chemistry parameters is recommended.

Keywords: reference interval, adolescent, clinical chemistry, Ethiopia

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Authors: Sajed Yaghoubnezhad, Mina Karimi, Seyede Marjan Modirkhazeni

Abstract:

The goal of this research was to study the relationship between codependency, perceived social support and depression in mothers of children with intellectual disability (ID). The correlational method was used in this study. The research population is comprised of mothers of educable children with ID in the age range of 25 to 61 years. From among this, a sample of 251 individuals, in the multistage cluster sampling method, was selected from educational districts in Tehran, who responded to the Spann-Fischer Codependency Scale (SFCDS), the Social Support Questionnaire and the Beck Depression Inventory (BDI). The findings of this study indicate that among mothers of children with ID depression has a positive and significant correlation with codependency (P<0.01, r=0.4) and a negative and significant correlation with the total score of social support (P<0.01, r=-0.34). Moreover, the results of stepwise multiple regression analysis showed that codependency is allocated a higher variance than social support in explaining depression (R²=0.023).

Keywords: codependency, social support, depression, mothers of children with ID

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Authors: Daphne Alroy-Thiberge

Abstract:

Trauma-impacted individuals present unique treatment challenges that include high reactivity, hyper-and hypo-arousal, poor adherence to therapy, as well as powerful transference and counter-transference experiences in therapy. This work provides an overview of the clinical tenets most often encountered in trauma-impacted individuals. Further, it provides readily applicable clinical techniques to optimize therapeutic rapport and facilitate accelerated positive mental health outcomes. Finally, integrated neuroscience and clinical evidence-based data are discussed to shed new light on crisis states in trauma-impacted individuals. This knowledge is utilized to provide effective and concrete interventions towards rapid and successful de-escalation of the impacted individual. A highly interactive, adult-learning-principles-based modality is utilized to provide an organic learning experience for participants. The information and techniques learned aim to increase clinical effectiveness, reduce staff injuries and burnout, and significantly enhance positive mental health outcomes and self-determination for the trauma-impacted individuals treated.

Keywords: clinical competencies, crisis interventions, psychotherapy techniques, trauma informed care

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Authors: Serhat Tuzun, Tufan Demirel

Abstract:

Multi-Criteria Decision Making (MCDM) is the modelling of real-life to solve problems we encounter. It is a discipline that aids decision makers who are faced with conflicting alternatives to make an optimal decision. MCDM problems can be classified into two main categories: Multi-Attribute Decision Making (MADM) and Multi-Objective Decision Making (MODM), based on the different purposes and different data types. Although various MADM techniques were developed for the problems encountered, their methodology is limited in modelling real-life. Moreover, objective results are hard to obtain, and the findings are generally derived from subjective data. Although, new and modified techniques are developed by presenting new approaches such as fuzzy logic; comprehensive techniques, even though they are better in modelling real-life, could not find a place in real world applications for being hard to apply due to its complex structure. These constraints restrict the development of MADM. This study aims to conduct a comprehensive analysis of preference methods in MADM and propose an approach based on information. For this purpose, a detailed literature review has been conducted, current approaches with their advantages and disadvantages have been analyzed. Then, the approach has been introduced. In this approach, performance values of the criteria are calculated in two steps: first by determining the distribution of each attribute and standardizing them, then calculating the information of each attribute as informational energy.

Keywords: literature review, multi-attribute decision making, operations research, preference method, informational energy

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Authors: S. Ghorbani, N. I. Polushin

Abstract:

In this study, an approach to identify factors affecting on surface roughness in a machining process is presented. This study is based on 81 data about surface roughness over a wide range of cutting tools (conventional, cutting tool with holes, cutting tool with composite material), workpiece materials (AISI 1045 Steel, AA2024 aluminum alloy, A48-class30 gray cast iron), spindle speed (630-1000 rpm), feed rate (0.05-0.075 mm/rev), depth of cut (0.05-0.15 mm) and tool overhang (41-65 mm). A single decision tree (SDT) analysis was done to identify factors for predicting a model of surface roughness, and the CART algorithm was employed for building and evaluating regression tree. Results show that a single decision tree is better than traditional regression models with higher rate and forecast accuracy and strong value.

Keywords: cutting condition, surface roughness, decision tree, CART algorithm

Procedia PDF Downloads 376