Analysing Lesbian, Gay, Bisexual, Transgender and Queer or Questioning (LQBTQ) Cyberbullying Using Unsupervised Associative Approach Text Analytics Technique

Cyberbullying has become one of the major threats in our society today due to the massive damage that it can cause not only in the cyber world and the internet-based business but also in the lives of many people. The sole purpose of cyberbullying is to hurt and humiliate someone by posting and sending threats online. However, recognition of cyberbullying has proved to be a hard and challenging task for information technologists. The main objective of this study is to analyze and decode the ambiguity of human language used in cyberbullying Lesbian, Gay, Bisexual, Transgender and Queer or Questioning (LGBTQ) victims and detect patterns and trends from the results to produce meaning and knowledge. This study will utilize an unsupervised associative approach text analysis technique that will be used to extract the relevant information from the unstructured text of cyberbullying messages. Furthermore, cyberbullying incidence patterns will be analyzed based on recognizing relationships and meaning between cyberbullying keywords with other words to generate knowledge discovery. “Fuck” and “Shit” account almost half of all cyberbullying words and appear more that 75 % in the dataset as the most frequently used words. Further, the terms “shit”+“hate”+ “fuck” with a positive lift value and “shit”+ “stupid” positive obtained the highest chance of togetherness / chance of utilizing both of these words to cyber bully. The combination of words / word patterns was considered abusive swearing is always considered rude when it is used to intimidate or humiliate someone. The output and results of this study will contribute to formulating future intervention to combat cyberbullying. Furthermore, the results can be utilized as a model in the development of a cyberbullying detection application based on the text relations / associations of words in the comments, replies, blog discussion and discussion groups across the social networks.

Application of Machine Learning in Pulmonary Function Assessment Where Are We Now and Where Are We Going?

Analysis of pulmonary function tests (PFTs) is an area where machine learning (ML) may benefit clinicians, researchers, and the patients. PFT measures spirometry, lung volumes, and carbon monoxide diffusion capacity of the lung (DLCO). The results are usually interpreted by the clinicians using discrete numeric data according to published guidelines. PFT interpretations by clinicians, however, are known to have inter-rater variability and the inaccuracy can impact patient care. This variability may be caused by unfamiliarity of the guidelines, lack of training, inadequate understanding of lung physiology, or simply mental lapses. A rules-based automated interpretation system can recapitulate expert’s pattern recognition capability and decrease errors. ML can also be used to analyze continuous data or the graphics, including the flow-volume loop, the DLCO and the nitrogen washout curves. These analyses can discover novel physiological biomarkers. In the era of wearables and telehealth, particularly with the COVID-19 pandemic restricting PFTs to be done in the clinical laboratories, ML can also be used to combine mobile spirometry results with an individual’s clinical profile to deliver precision medicine. There are, however, hurdles in the development and commercialization of the ML-assisted PFT interpretation programs, including the need for high quality representative data, the existence of different formats for data acquisition and sharing in PFT software by different vendors, and the need for collaboration amongst clinicians, biomedical engineers, and information technologists. Hurdles notwithstanding, the new developments would represent significant advances that could be the future of PFT, the oldest test still in use in clinical medicine.

Adoption of Koha Integrated Library System (ILS) for the Automation of Umaru Musa Yar’adua University Library, Katsina, Nigeria: Problems and Prospects

This study attempted to explore the gradual advancement of modern technology in libraries, it distinguished old and new innovations, creative efforts of librarians and information technologists through the various generations of automation revolution. The study also identify various components of the Integrated Library System (ILS) or Library Management System (LMS) which are used or being used in Umaru Musa Yar’adua University (UMYU) library as well as the services automated by the system. The study also identifies the exact reasons for adopting KOHA in UMYU library. It also explains the impact, challenges associated with the University library automation system. The study adopted quantitative approach as research paradigm; with survey as research methods. Questionnaires were the instrument used for data collection. The population of 42 library staff was used for the study. The data for the study were analyzed using tables and frequencies. From the findings of the study the two main services fully automated were the Circulation and Cataloguing, the library adopted the use of the KOHA ILS as it was a free open source and secondly for greater opportunities and innovation. However, retrospective conversion and Low Level of Literacy were the major challenges and a setback for the KOHA ILS implementation in the library understudy. The study recommended the need for the increase investment in the automation project to speed up the implementation of automation systems.

Clinical Decision Support Systems in Otolaryngology–Head and Neck Surgery: A State of the Art Review

Objective To offer practical, evidence-informed knowledge on clinical decision support systems (CDSSs) and their utility in improving care and reducing costs in otolaryngology–head and neck surgery. This primer on CDSSs introduces clinicians to both the capabilities and the limitations of this technology, reviews the literature on current state, and seeks to spur further progress in this area. Data Sources PubMed/MEDLINE, Embase, and Web of Science. Review Methods Scoping review of CDSS literature applicable to otolaryngology clinical practice. Investigators identified articles that incorporated knowledge-based computerized CDSSs to aid clinicians in decision making and workflow. Data extraction included level of evidence, Osheroff classification of CDSS intervention type, otolaryngology subspecialty or domain, and impact on provider performance or patient outcomes. Conclusions Of 3191 studies retrieved, 11 articles met formal inclusion criteria. CDSS interventions included guideline or protocols support (n = 8), forms and templates (n = 5), data presentation aids (n = 2), and reactive alerts, reference information, or order sets (all n = 1); 4 studies had multiple interventions. CDSS studies demonstrated effectiveness across diverse domains, including antibiotic stewardship, cancer survivorship, guideline adherence, data capture, cost reduction, and workflow. Implementing CDSSs often involved collaboration with health information technologists. Implications for Practice While the published literature on CDSSs in otolaryngology is finite, CDSS interventions are proliferating in clinical practice, with roles in preventing medical errors, streamlining workflows, and improving adherence to best practices for head and neck disorders. Clinicians may collaborate with information technologists and health systems scientists to develop, implement, and investigate the impact of CDSSs in otolaryngology.

Intensive Care Unit design; from advance to basic

Optimum ICU design has pivotal role in critical care delivery that has major impact on physical and psychological health of the patients, physicians and other related staff. Its structure formation is complex and demands the dedicated involvement of not only care providers but also a trained and multi-professional team of architect, engineer and information technologists, etc. This paper tracks the journey from traditional design to recent advances in building the intensive care unit. The limitations in ICU design observed in the lower to middle income countries will also be discussed in this review. Specialist hospital architects are scarce in these countries and the ordinary civil engineering does not impart adequate coaching on matters related to lay-out plans as well as the various minute details about fittings and provisions. Hence, it becomes imperative for the anesthesiologists and other healthcare providers to come to guide and assistance to the architects involved in designing the blue prints. It may only be possible if they have adequate knowledge and professional experience.Citation: Butt MN, Khan MF. Intensive Care Unit design; from advance to basic. Anaesth Pain & Intensive Care 2018;22 Suppl 1:S17-S20

The Future of Wearable Technologies and Remote Monitoring in Health Care

Mobile technology has become a ubiquitous part of everyday life and is changing the way we offer clinical care and perform clinical research. We have unprecedented access to data for one’s self-care as well as for sharing with health care providers. Meeting the challenge posed by the influx of wearable device data requires a multidisciplinary team of researchers, clinicians, software developers, information technologists, and statisticians. Although the possibility of what can be achieved with the ever-evolving wearable technologies seems to be unlimited, regulatory agencies have provided a framework to establish standards for clinical applications, which will also affect research applications. Clinical programs and electronic medical records vendors should prepare to establish a framework to implement these technologies into clinicians’ workflow and to allow feedback to measure the impact on clinical outcome. In this article, we discuss how a new brand of multidisciplinary care is evolving around mobile health devices and present a vision of up-and-coming technology in this space.

Developing a conceptual model for insider threat

This paper sets out 99 case studies of insider attacks that took place in the UK. The study involved interviewing investigators, heads of security, information technologists, law enforcement, security officers, human resource managers, line managers, and coworkers who knew the insider. The analysis elucidates how to identify insiders and pathways to these attacks. It also highlights examples of archetypal insiders, in addition to the ‘disgruntled employee’ (e.g., ‘the show off’, ‘the career criminal’, ‘the addict’, etc.). In contrast to other studies, this study highlights multiple pathways to an attack. A conceptual model is set out that considers indicators (both physical and cyber) that might be monitored in an insider risk detection programme. The model stressors need to continuously seek out methods to close down opportunities as well as to monitor behavioural change. It also elucidates potential deterrence and prevention strategies for organisations to consider in an ethical and legal manner.