End-user Training Research Articles

Minimizing Business Disruption During Enterprise End-Point OS Upgrade while Maintaining a Robust Security Posture

The deployment of a major end-point operating system (OS) upgrade presents significant challenges for enterprise organizations, requiring a comprehensive strategy to minimize business disruption and maintain a robust security posture. Beyond the operational complexities of managing user productivity and application compatibility, organizations must also proactively address the critical security risks associated with such large-scale technology transitions. Cybercriminals often target organizations undergoing major IT changes, seeking to exploit vulnerabilities that may arise due to shifts in the OS architecture, user workflows, and security controls. This paper outlines practical strategies for executing successful OS upgrade projects that balance operational resilience and cyber risk management. Key focus areas include proactive management of end-point security, comprehensive contingency planning and rollback procedures, strategies to sustain productivity and business continuity, effective end-user training and communication, and valuable insights into the next- generation OS deployment. By focusing on these critical aspects, organizations can navigate major OS upgrade initiatives while preserving vigorous business operations, enhancing end-user experience, and safeguarding sensitive data and systems from costly security incidents.

Toward a responsible future: recommendations for AI-enabled clinical decision support.

Integrating artificial intelligence (AI) in healthcare settings has the potential to benefit clinical decision-making. Addressing challenges such as ensuring trustworthiness, mitigating bias, and maintaining safety is paramount. The lack of established methodologies for pre- and post-deployment evaluation of AI tools regarding crucial attributes such as transparency, performance monitoring, and adverse event reporting makes this situation challenging. This paper aims to make practical suggestions for creating methods, rules, and guidelines to ensure that the development, testing, supervision, and use of AI in clinical decision support (CDS) systems are done well and safely for patients. In May 2023, the Division of Clinical Informatics at Beth Israel Deaconess Medical Center and the American Medical Informatics Association co-sponsored a working group on AI in healthcare. In August 2023, there were 4 webinars on AI topics and a 2-day workshop in September 2023 for consensus-building. The event included over 200 industry stakeholders, including clinicians, software developers, academics, ethicists, attorneys, government policy experts, scientists, and patients. The goal was to identify challenges associated with the trusted use of AI-enabled CDS in medical practice. Key issues were identified, and solutions were proposed through qualitative analysis and a 4-month iterative consensus process. Our work culminated in several key recommendations: (1) building safe and trustworthy systems; (2) developing validation, verification, and certification processes for AI-CDS systems; (3) providing a means of safety monitoring and reporting at the national level; and (4) ensuring that appropriate documentation and end-user training are provided. AI-enabled Clinical Decision Support (AI-CDS) systems promise to revolutionize healthcare decision-making, necessitating a comprehensive framework for their development, implementation, and regulation that emphasizes trustworthiness, transparency, and safety. This framework encompasses various aspects including model training, explainability, validation, certification, monitoring, and continuous evaluation, while also addressing challenges such as data privacy, fairness, and the need for regulatory oversight to ensure responsible integration of AI into clinical workflow. Achieving responsible AI-CDS systems requires a collective effort from many healthcare stakeholders. This involves implementing robust safety, monitoring, and transparency measures while fostering innovation. Future steps include testing and piloting proposed trust mechanisms, such as safety reporting protocols, and establishing best practice guidelines.

Training and Familiarization with Industrial Exoskeletons: A Review of Considerations, Protocols, and Approaches for Effective Implementation.

Effective training programs are essential for safely integrating exoskeletons (EXOs) in industrial workplaces. Since the effects of wearable systems depend highly upon their proper use, lack of training of end-users may cause adverse effects on users. We reviewed articles that incorporated training and familiarization protocols to train novices on proper operation/use of EXOs. Findings showed variation in training methods that were implemented to train study participants in EXO evaluation studies. Studies also indicate that multiple (up to four) sessions may be needed for novice EXO wearers to match movement patterns of experts, and training can offer benefits in enhancing motor learning in novices. Biomechanical assessments and ergonomic evaluations can be helpful in developing EXO-specific training protocols by determining training parameters (duration/number of sessions and task difficulty). Future directions include development of personalized training approaches by assessing user behavior/performance through integration of emerging sensing technologies. Application of simulators and use of data-driven approaches for customizing training protocols to individuals, tasks, and EXO design are provided along with a comprehensive training framework. Discussed elements in this article can be helpful to exoskeleton researchers in familiarizing novice users to EXOs prior to evaluation, and to practitioners in developing protocols for training workforce.

MHealth learning strategies to support behaviour change in individuals using wheelchairs and/or scooters: a systematic review.

The purpose of this systematic review of the literature is to build understanding of the key elements and recommendations for the design of mHealth technology for individuals using wheelchairs and/or scooters and identify key features associated with the use of mHealth to support healthy behaviour changes for this population. Eight major electronic databases were systematically searched to identify mobile health (mHealth) interventions, which targeted adult WC/S users. Independent reviewers used Endnote and Covidence to manage articles meeting review criteria and to exclude duplicates. A quality assessment was conducted on each included article. Nine articles describing studies with diverse study designs met criteria to be included in this review. Several interactive application intervention features, such as participant collaboration and goal setting, and key technical features to support mHealth app development and utilisation were identified. Results found intuitive and simple designs of mHealth apps, with the ability to customise to support learning styles and preferences, support usability and acceptability by participants. More research is needed to evaluate best practices to support initial training of end-users, mHealth apps' ability to support long-term behaviour change and maintenance, and the understanding of active ingredients in complex interventions that include mHealth apps. Both interactive mHealth application intervention and technical features support healthy behaviour change among individuals using wheelchairs and scooters.

Design principles for e-learning platforms featuring higher-education students’ enterprise systems end-user training

Enterprise systems are complex information systems that are inevitable for companies’ success. As enterprise systems are only successful when used continuously and efficiently by end-users, knowledge on how to use them has become an important skill for employees. Research and practice favor an early obtainment of these skills for employees. Thus, it is usual to train students in enterprise systems usage before they start their professional career. Even though in organizational settings e-learning based approaches gain momentum, adapting design instances of multi-purpose platforms like Udacity, Udemy or Coursera existing approaches directed at students are scarce. Nevertheless, a well-informed e-learning platform design can support the learning process. Therefore, we investigate the design of e-learning platforms featuring students’ enterprise system end-user training. To address the lack of guidance on designing such e-learning platforms, we proposed four meta-requirements and ten design principles to increase students’ learning success on e-learning platforms focusing on students’ end-user training. To achieve this goal and to ground our results on empiricism, we collected data about e-learning-platform design from three data sources: (1) We reviewed the existing literature, (2) carried out a multi-case analysis, and (3) derived insights from implementing an e-learning platform for students’ end-user training and thereby demonstrating the applicability of the design principles. Finally, we evaluated the implementation. Following the design principles, learning success should be increased by a flexible learning environment with easy access and use, propelled motivation, and fostered information exchange.

Facilitators and Barriers in the Implementation and Adoption of Patient-Reported Outcomes Measurements in Daily Practice

ObjectivesAt the Erasmus Medical Center, patient-reported outcomes measures (PROMs) are implemented on a hospital-wide scale. However, less than half of the patients and healthcare professionals (HCPs) use these PROMs. Therefore, this study aimed to investigate facilitators and barriers for adoption of PROMs to develop guidance around implementation. MethodsA mixed-methods study with a combination of interviews and focus groups and questionnaires was conducted, involving patients, both PROM nonresponders and PROM responders, HCPs, and medicine students and nurse specialists in training (hereafter “students”). Interview transcripts were subjected to thematic content analysis. Subsequently, questionnaires were developed and presented to all stakeholders to validate the findings. Finally, identified themes and implementation recommendations were presented in a final questionnaire to the Value-Based Healthcare Erasmus Medical Center expert group to prioritize findings. ResultsInterviews were conducted with 15 patients, 14 HCPs and 4 students, and 2 focus groups with 5 students. The questionnaire was completed by 370 of 999 responders (37.0%), 173 of 1395 nonresponders (12.5%), and 44 of 194 HCPs (22.7%), and 40 students were reached via an open link. The identified facilitators and barriers were grouped into 4 overarching themes: training on PROMs at different levels in the education of (future) HCPs, motivate and reduce the burden for the HCP, implement generic and disease-specific PROMs simultaneously, and motivate, activate, and reduce the patient burden. ConclusionsProviding end users with digital tools, implementation support, and a clear hospital-wide vision is important, yet this does not guarantee successful adoption of PROMs. Successful adoption necessitates ongoing efforts to engage, motivate, and train end users.

Ethical Considerations in the Development of AI-Powered Healthcare Assistants

Advances in the field of artificial intelligence (AI) have led to the development of increasingly sophisticated health assistants that can provide support in diagnosis, treatment and general health management. However, as with the use of new technologies in the healthcare context, ethical considerations play an important role in the design, development, and implementation of AI-based health assistants. In this paper, we investigate various ethical considerations associated with the development of AI-based healthcare assistants. We explore issues such as the privacy and security of patient data, transparency and accountability in decision making, and the social and psychological impact of reliance on technology in the healthcare context. We also discuss efforts that can be taken to address these ethical challenges, including the development of appropriate regulatory guidelines, ongoing monitoring of system performance, and education and training for health professionals and end users. By seriously considering ethical aspects in the development of AI-based healthcare assistants, we hope to ensure that this technology can provide maximum benefit to patients while maintaining the ethical and moral values that underlie good healthcare practices.

An Investigation on the Use of Electronic Resources by Faculty and Research Scholars of National Law Universities of North India

The purpose of this study is to examine how research scholars and faculty at National Law Universities of North India use and are aware of electronic resources for legal information. The parameters used to determine the level of awareness of e-resources include the easiest way to access legal e-resources, obstacles and difficulties encountered when doing so, the most popular online legal database, and recommendations for e-resource promotion. A well-structured questionnaire intended for faculty members and research scholars at a select National Law Universities of North India was used to gather the necessary data for the study. According to the study, the most popular online databases are Manupatra and SCC Online, while the most popular e-resources are law reform reports and case law databases. Upgrading of ICT facilities, the acquisition of new databases and e-resources, and the planning of end-user training programs are all ways to improve end-user awareness and utilization of e-resources. The study further highlighted the need for NLUs to maintain a set of guidelines and policies regarding encouraging users to use electronic resources in order to improve usage.

Towards a Hybrid Security Framework for Phishing Awareness Education and Defense

The rise in generative Artificial Intelligence (AI) has led to the development of more sophisticated phishing email attacks, as well as an increase in research on using AI to aid the detection of these advanced attacks. Successful phishing email attacks severely impact businesses, as employees are usually the vulnerable targets. Defense against such attacks, therefore, requires realizing defense along both technological and human vectors. Security hardening research work along the technological vector is few and focuses mainly on the use of machine learning and natural language processing to distinguish between machine- and human-generated text. Common existing approaches to harden security along the human vector consist of third-party organized training programmes, the content of which needs to be updated over time. There is, to date, no reported approach that provides both phishing attack detection and progressive end-user training. In this paper, we present our contribution, which includes the design and development of an integrated approach that employs AI-assisted and generative AI platforms for phishing attack detection and continuous end-user education in a hybrid security framework. This framework supports scenario-customizable and evolving user education in dealing with increasingly advanced phishing email attacks. The technological design and functional details for both platforms are presented and discussed. Performance tests showed that the phishing attack detection sub-system using the Convolutional Neural Network (CNN) deep learning model architecture achieved the best overall results: above 94% accuracy, above 95% precision, and above 94% recall.

A Literature Review of Collaborative Virtual Environments: Impacts, Design Principles, and Challenges

Aim/Purpose: The purpose of this research is to evaluate the available literature on Collaborative Virtual Environments (CVEs). It aims to investigate the impacts, guiding principles, and problems of CVEs, giving light to their revolutionary potential in a variety of sectors, such as education, healthcare, and gaming. Background: CVEs have received a lot of interest in recent years because of their potential to change how people interact and cooperate in virtual settings. It has the potential to increase collaboration, learning experiences, and productivity across numerous areas. Methodology: This study comprehensively analyzes existing literature on CVEs, highlighting their ability to significantly change several fields, such as education, healthcare, and gaming. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards were followed to ensure a clear and methodical approach to the literature review. The search technique targeted the SCOPUS database for articles published from 2009 to 2022, utilizing specific keywords about CVEs. This was followed by a thorough two-stage screening procedure based on specified inclusion and exclusion criteria, ensuring only relevant research was evaluated. Contribution: This literature review contributes by providing a thorough review of the current state of the art in the field of CVEs. It synthesizes previous research and offers insights into the consequences, guiding principles, and problems of CVEs in different domains. Findings: The research results demonstrate the wide range of uses for CVEs and their ability to promote enhanced cooperation, learning, and productivity. Current obstacles have been identified, and a set of guiding principles for implementing CVEs has been provided. A clear and reproducible foundation for future research in this area was found through a detailed explanation of the search approach and criteria used to select studies. The literature review concludes with practical suggestions for practitioners in many fields, emphasizing the need to consider CVEs to improve cooperation and productivity. Recommendations for Practitioners: To improve cooperation and productivity, CVEs should be considered by practitioners in education, healthcare, gaming, and industry. Best practices and recommendations for the successful usage of CVEs in various areas must be established. End-user training and assistance are critical for maximizing the benefits of CVE technology. Recommendation for Researchers: Additional study is required to investigate the long-term consequences and durability of CVE solutions, the creation of new technologies and methods to overcome the stated CVE adoption problems, and multidisciplinary collaboration to harness CVEs in innovative ways. Impact on Society: The review emphasizes CVEs’ potential social benefit in fostering cooperation, improving learning experiences, and increasing productivity. The widespread use of CVE technology may result in more efficient and productive ways of communicating and working in virtual worlds. Future Research: Future studies in this field should concentrate beyond the study’s period (2022), investigating the changing environment of CVEs, examining the effects of developing technologies and trends on CVEs, and evaluating CVE technology’s scalability and accessibility for greater societal usage.

Challenges of Implementing Enterprise Resource Planning and The Role of Knowledge Management

Using the National Youth Development Agency (NYDA) as a case study, this paper considers the challenges of implementing enterprise resource planning (ERP). Data was collected from management and employees using both qualitative and quantitative research techniques. The study established challenges beyond the technical issues, these included: misalignment of the system to the organisation processes, product quality and unavailability of the system’s helpdesk, lack of top management support, and lack of pilot testing, insufficient end-user training, resistance to change management, lack of processes integration, poor technology planning and security and risk matters. Furthermore, the management process that resonates on knowledge transfer, knowledge management, and change management poses a complex challenge in the implementation of ERP. The study recommends the alignment of the user environment, effective change management, and knowledge strategies that are essential to drive ERP. It is also recommended to close the gap between what ERP offers and what end users want and can do.

Speech Recognition and Sending Alert Message If Abusive Words are Detected

Abstract: This paper introduces an innovative approach to bolstering the field of speech recognition. Speech recognition, a pivotal process in facilitating computer systems' understanding and response to natural language commands, has garnered considerable importance in today's digital landscape. Our novel method aims to enable users to issue voice commands with enhanced accuracy and efficiency. This approach encompasses several critical steps: the intake of a single audio input, effective noise reduction, and the utilization of pattern matching for audio recognition. To fortify the system's robustness, we've integrated an error tolerance mechanism capable of accommodating human errors and mitigating environmental noise.What sets our method apart is its ability to circumvent the need for storing extensive audio data for matching, leading to a substantial reduction in both space and time complexity when compared to conventional systems. In our experiments, we have exclusively employed a database containing an array of predefined voice patterns, effectively eliminating the necessity for end-user training.

Addressing complexity when developing an education program for the implementation of a stroke Electronic Medical Record (EMR) enhancement

BackgroundDigital interventions in health services often fail due to an underappreciation of the complexity of the implementation. This study develops an approach to address complexity through an evidenced-based, theory-driven education and implementation program for an Electronic Medical Record (EMR) digital enhancement for acute stroke care.MethodsAn action research approach was used to design, develop, and execute the education and implementation program over several phases, with iterative changes over time. The study involved collaboration with multiple statewide and local key stakeholders and was conducted across two tertiary teaching hospitals and a regional hospital in Australia.ResultsInsights were gained over five phases. Phase 1 involved a review of evidence that supported blended learning strategies for the education and training of staff end-users. In Phase 2, contextual assessment was conducted via observation of study sites, providing awareness of local context variability and insight into key implementation considerations. The Non-adoption, Abandonment, Scale-Up, Spread and Sustainability (NASSS) framework assisted in Phase 3 to identify and manage the key domains of complexity. Phase 4 involved the design of the program which included group-based training and an e-learning package, endorsed and evaluated by key leaders. Throughout implementation in Phase 5, further barriers were identified, and iterative changes were tailored to each context.ConclusionsThe NASSS framework, combined with a multi-phased approach employing blended learning techniques, context evaluations, and iterative modifications, can serve as a model for generating theory-driven and evidence-based education strategies that adresss the complexity of the implementation process and context.

Real-time hand interaction and self-directed machine learning agents in immersive learning environments

Integration of extended reality (XR) in education is becoming popular to transform the traditional classroom with immersive learning environments. The adoption of immersive learning is accelerating as an innovative approach for science and engineering subjects. With new powerful interaction techniques in XR and the latest developments in artificial intelligence, interactive and self-directed learning are becoming important. However, there is a lack of research exploring these emerging technologies research with kinesthetic learning or “hands-one learning" as a pedagogical approach using real-time hand interaction and agent-guided learning in immersive environments. This paper proposes a novel approach that uses machine learning agents to facilitate interactive kinesthetic learning in science and engineering education through real-time hand interaction in the virtual world. To implement the following approach, this paper uses a chemistry-related case study and presents a usability evaluation conducted with 15 expert reviewers and 2 subject experts. NASA task load index is used for cognitive workload measurement, and the technology acceptance model is used for measuring perceived ease of use and perceived usefulness in the evaluations. The evaluation with expert reviewers proposed self-directed learning using trained agents can help in the end-user training in learning technical topics and controller-free hand interaction for kinesthetic tasks can improve hands-on learning motivation in virtual laboratories. This success points to a novel research area where agents embodied in an immersive environment using machine learning techniques can forge a new pedagogical approach where they can act as both teacher and assessor.

Airport Common-Use Check-in Operations: A Novel and Efficient Model

This paper examines the capacity problems of common-use environment service improvement and airport passenger services in line with information technology (IT) issues. There are many time-critical processes in the airport terminal for the necessary airport passenger flow processes that IT service design aims to support it. Many flow processes can be designed under several functions while international, domestic, or general aviation cases. The current approaches have been based on the standard industrial methods based on the Information Technology Infrastructure Library (ITIL) practices. However, this infrastructure library practices’ distinct general industrial foundations and airport time-critical processes could not fit customer expectations. This research offers an approach by adding a pre-layer with a user certification rather than fixing the problems on the ground. Although the proposed novel model does not conflict with the ITIL practices, it primarily develops the practices by coinciding with them a certificated training of end users to establish a positive passenger experience and helping the profitability of the airport. The offered model simulation results show that the Airport IT Service helpdesk and field team instantaneous utilization average was reduced from 96% to 28%, and the field team queue duration during the airport peak hours was 26 minutes to 2 minutes. This study demonstrates that the airport IT support service design should be reconsidered during its passenger service operation.

Factors influencing the implementation of decision support systems for antibiotic prescription in hospitals: a systematic review

BackgroundAntibiotic resistance is a major health threat. Inappropriate antibiotic use has been shown to be an important determinant of the emergence of antibiotic resistance. Decision support systems for antimicrobial management can support clinicians to optimize antibiotic prescription.ObjectiveThe aim of this systematic review is to identify factors influencing the implementation of decision support systems for antibiotic prescription in hospitals.MethodsA systematic search of factors impeding or facilitating successful implementation of decision support systems for antibiotic prescription was performed in January 2022 in the databases PubMed, Web of Science and The Cochrane Library. Only studies were included which comprised decision support systems in hospitals for prescribing antibiotic therapy, published in English with a qualitative, quantitative or mixed-methods study design and between 2011 and 2021. Factors influencing the implementation were identified through text analysis by two reviewers.ResultsA total of 14 publications were identified matching the inclusion criteria. The majority of factors relate to technological and organizational aspects of decision support system implementation. Some factors include the integration of the decision support systems into existing systems, system design, consideration of potential end-users as well as training and support for end-users. In addition, user-related factors, like user attitude towards the system, computer literacy and prior experience with the system seem to be important for successful implementation of decision support systems for antibiotic prescription in hospitals.ConclusionThe results indicate a broad spectrum of factors of decision support system implementation for antibiotic prescription and contributes to the literature by identifying important organizational as well as user-related factors. Wider organizational dimensions as well as the interaction between user and technology appear important for supporting implementation.

Technical Innovation in Critical Care in a World of Constraints: Lessons from the COVID-19 Pandemic.

The COVID-19 crisis was characterized by a massive need for respiratory support, which has unfortunately not been met globally. This situation mimicked those which gave rise to critical care in the past. Since the polio epidemic in the 50's, the technological evolution of respiratory support has enabled health professionals to save the lives of critically-ill patients worldwide every year. However, much of the current innovation work has turned around developing sophisticated, complex, and high-cost standards and approaches whose resilience is still questionable upon facing constrained environments or contexts, as seen in resuscitation work outside intensive care units, during pandemics, or in low-income countries. Ventilatory support is an essential life-saving tool for patients with respiratory distress. It requires an oxygen source combined to a ventilatory assistance device, an adequate monitoring system, and properly trained caregivers to operate it. Each of these elements can be subject to critical constraints, which we can no longer ignore. The innovation process should incorporate them as a prima materia, whilst focusing on the core need of the field using the concept of frugal innovation. Having a universal access to oxygen and respiratory support, irrespective of the context and constraints, necessitates: i) developing cost-effective, energy-efficient, and maintenance-free oxygen generation devices; ii) improving the design of non-invasive respiratory devices (for example, with oxygen saving properties); iii) conceiving fully frugal ventilators and universal monitoring systems; iv) broadening ventilation expertise by developing end-user training programs in ventilator assistance. The frugal innovation approach may give rise to a more resilient and inclusive critical care system. This paradigm shift is essential for the current and future challenges.

Intensive Care Unit Physicians’ Perspectives on Artificial Intelligence–Based Clinical Decision Support Tools: Preimplementation Survey Study

Artificial intelligence-based clinical decision support (AI-CDS) tools have great potential to benefit intensive care unit (ICU) patients and physicians. There is a gap between the development and implementation of these tools. We aimed to investigate physicians' perspectives and their current decision-making behavior before implementing a discharge AI-CDS tool for predicting readmission and mortality risk after ICU discharge. We conducted a survey of physicians involved in decision-making on discharge of patients at two Dutch academic ICUs between July and November 2021. Questions were divided into four domains: (1) physicians' current decision-making behavior with respect to discharging ICU patients, (2) perspectives on the use of AI-CDS tools in general, (3) willingness to incorporate a discharge AI-CDS tool into daily clinical practice, and (4) preferences for using a discharge AI-CDS tool in daily workflows. Most of the 64 respondents (of 93 contacted, 69%) were familiar with AI (62/64, 97%) and had positive expectations of AI, with 55 of 64 (86%) believing that AI could support them in their work as a physician. The respondents disagreed on whether the decision to discharge a patient was complex (23/64, 36% agreed and 22/64, 34% disagreed); nonetheless, most (59/64, 92%) agreed that a discharge AI-CDS tool could be of value. Significant differences were observed between physicians from the 2 academic sites, which may be related to different levels of involvement in the development of the discharge AI-CDS tool. ICU physicians showed a favorable attitude toward the integration of AI-CDS tools into the ICU setting in general, and in particular toward a tool to predict a patient's risk of readmission and mortality within 7 days after discharge. The findings of this questionnaire will be used to improve the implementation process and training of end users.

DEVELOPMENT OF DIGITAL BANKING IN THE STRUCTURE OF THE BANK'S REMOTE SERVICE MECHANISM UNDER MARTIAL LAW

The article emphasizes the importance of modern digital development of the banking sector towards the digitalization of the remote banking mechanism. The author considers the impact of remote banking on the positions of banks, support for the economy and the main aspects of its functioning in Ukraine. Special attention is paid to the main cybersecurity issues in the e-banking mechanism: shortage of personnel, lack of awareness of employees, lack of an appropriate quality budget, credentials problem areas, gaps in mobile applications of banks. The study identifies key elements of remote banking during martial law, such as reducing the territorial network of banks, developing technological solutions, operational stability, depositor confidence, investing in cybersecurity and staff. The article reflects the challenges and threats to the current functioning of Ukrainian banks during martial law, and highlights the peculiarities of transformations at the current stage of the remote banking mechanism. Attention is drawn to the importance of introducing practical trainings, case studies, and cyberattack simulations in the training of staff and customers; the importance of using artificial intelligence and machine learning is also emphasized. Artificial intelligence and machine learning are important for recognizing and countering cyber threats in real time. Training of end users - awareness - is an important cybersecurity asset in the RBS mechanism, depending on their habits and behavior. The author suggests stages of training in the form of a webinar or interactive seminars for greater efficiency and the ability to answer questions from participants. The importance of all consumers of bank services of different age groups is emphasized. The author extends the use of artificial intelligence in the areas of creating predictive models, performing natural language processing for analyzing unstructured data, creating systems for full automation, providing reinforcement learning, implementing generative models for fraud detection, combating money laundering, and analyzing customer behavior. It is concluded that the use of innovative technologies will allow banks to automate the detection of abnormal and suspicious activities, ensuring a high level of security and protection of financial transactions. The author proposes to improve the current mechanism of the digital environment on the basis of cyber insurance, and indicates the practical aspects of the functioning of the insurance scheme with the participation of a bank as an insurance agent. For greater effectiveness of this type of insurance, it is proposed to focus on the risk of extortion - phishing (Internet extortion, fake payment sites), vishing (telephone fraud), withdrawal of funds from a lost/stolen card, etc.

Knowledge, perceptions, and expectations of Artificial intelligence in radiography practice: A global radiography workforce survey

BackgroundArtificial Intelligence (AI) technologies have already started impacting clinical practice across various settings worldwide, including the radiography profession. This study is aimed at exploring a world-wide view on AI technologies in relation to knowledge, perceptions, and expectations of radiography professionals. MethodsAn online survey (hosted on Qualtrics) on key AI concepts was open to radiography professionals worldwide (August 1st to December 31st 2020). The survey sought both quantitative and qualitative data on topical issues relating to knowledge, perceptions, and expectations in relation to AI implementation in radiography practice. Data obtained was analysed using the Statistical Package for Social Sciences (SPSS) (v.26) and the six-phase thematic analysis approach. ResultsA total of 314 valid responses were obtained with a fair geographical distribution. Of the respondents, 54.1% (157/290) were from North America and were predominantly clinical practicing radiographers (60.5%, 190/314). Our findings broadly relate to different perceived benefits and misgivings/shortcomings of AI implementation in radiography practice. The benefits relate to enhanced workflows and optimised workstreams while the misgivings/shortcomings revolve around de-skilling and impact on patient-centred care due to over-reliance on advanced technology following AI implementation. DiscussionArtificial intelligence is a tool but to operate optimally it requires human input and validation. Radiographers working at the interface between technology and the patient are key stakeholders in AI implementation. Lack of training and of transparency of AI tools create a mixed response of radiographers when they discuss their perceived benefits and challenges. It is also possible that their responses are nuanced by different regional and geographical contexts when it comes to AI deployment. Irrespective of geography, there is still a lot to be done about formalised AI training for radiographers worldwide. This is a vital step to ensure safe and effective AI implementation, adoption, and faster integration into clinical practice by healthcare workers including radiographers. ConclusionAdvancement of AI technologies and implementation should be accompanied by proportional training of end-users in radiography and beyond. There are many benefits of AI-enabled radiography workflows and improvement on efficiencies but equally there will be widespread disruption of traditional roles and patient-centred care, which can be managed by a well-educated and well-informed workforce.