Description:
Background: This regional pilot site ‘end-user attitudes’ study explored nurses’ experiences and impressions of using the Nurses’ Behavioural Assistant (NBA) (a knowledge-based, interactive ehealth system) to assist them to better respond to behavioural and psychological symptoms of dementia (BPSD) and will be reported here. Methods: Focus groups were conducted, followed by a four-week pilot site ‘end-user attitudes’ trial of the NBA at a regional aged care residential facility (ACRF). Brief interviews were conducted with consenting nursing staff. Results: Focus group feedback (N = 10) required only minor cosmetic changes to the NBA prototype. Post pilot site end-user interview data (N = 10) indicated that the regional ACRF nurses were positive and enthusiastic about the NBA, however several issues were also identified. Conclusions: Overall the results supported the utility of the NBA to promote a person centred care approach to managing BPSD. Slight modifications may be required to maximise its uptake across all ACRF nursing staff.
Description:
In healthcare systems, medical devices help physicians and specialists in diagnosis, prognosis, and therapeutics. As research shows, validation of medical devices is significantly optimized by accurate signal processing. Biomedical Signal and Image Processing in Patient Care is a pivotal reference source for progressive research on the latest development of applications and tools for healthcare systems. Featuring extensive coverage on a broad range of topics and perspectives such as telemedicine, human machine interfaces, and multimodal data fusion, this publication is ideally designed for academicians, researchers, students, and practitioners seeking current scholarly research on real-life technological inventions. In healthcare systems, medical devices help physicians and specialists in diagnosis, prognosis, and therapeutics. As research shows, validation of medical devices is significantly optimized by accurate signal processing. Biomedical Signal and Image Processing in Patient Care is a pivotal reference source for progressive research on the latest development of applications and tools for healthcare systems. Featuring extensive coverage on a broad range of topics and perspectives such as telemedicine, human machine interfaces, and multimodal data fusion, this publication is ideally designed for academicians, researchers, students, and practitioners seeking current scholarly research on real-life technological inventions.
Description:
Intelligent business analytics is an emerging technology that has become a mainstream market adopted broadly across industries, organizations, and geographic regions. Intelligent business analytics is a current focus for research and development across academia and industries and must be examined and considered thoroughly so businesses can apply the technology appropriately. The Handbook of Research on Foundations and Applications of Intelligent Business Analytics examines the technologies and applications of intelligent business analytics and discusses the foundations of intelligent analytics such as intelligent mining, intelligent statistical modeling, and machine learning. Covering topics such as augmented analytics and artificial intelligence systems, this major reference work is ideal for scholars, engineers, professors, practitioners, researchers, industry professionals, academicians, and students. Intelligent business analytics is an emerging technology that has become a mainstream market adopted broadly across industries, organizations, and geographic regions. Intelligent business analytics is a current focus for research and development across academia and industries and must be examined and considered thoroughly so businesses can apply the technology appropriately. The Handbook of Research on Foundations and Applications of Intelligent Business Analytics examines the technologies and applications of intelligent business analytics and discusses the foundations of intelligent analytics such as intelligent mining, intelligent statistical modeling, and machine learning. Covering topics such as augmented analytics and artificial intelligence systems, this major reference work is ideal for scholars, engineers, professors, practitioners, researchers, industry professionals, academicians, and students.
Description:
Texture image classification is very useful in many domains. It has been tried using statistical, spectral and structural approaches. A novel Pixel N-grams technique has emerged for image feature extraction recently. The aim of this paper is to analyse the efficacy of Pixel N-grams technique for texture image classification in comparison with the traditional techniques namely Intensity histogram, Haralick’s features based on co-occurrence matrix and state-of-the-art Bag-of-Visual-Words (BoVW). The experiments were carried out on the benchmark UIUC texture dataset using SVM classifier. The classification performance was compared using Fscore, Recall and Precision. The classification results using Pixel N-gram were significantly better than that using Intensity histogram and Haralick features whereas, they were comparable with the BoVW approach.
Description:
Drawing on information gathered from scoping interviews with graduate recruiters and industry experts in Australia, this study extends our understanding of how employers, rather than researchers, describe the desired work-ready skills for graduate/entry level roles in the Australian information and communication technology (ICT) industry. Contrary to the developing literature on work-readiness, the findings showed that the skills which contribute to work-readiness should not be limited to field-specific knowledge, skills and cognitive skills, but that they should be extended to include affective skills or personal attributes and behaviors, such as selfefficacy, willingness to learn, disposition, tolerance and integrity. Results have practical implications for developing academic programs aimed at enhancing cognitive and affective skills among IT graduates for employment potential and successful transition into work.
Description:
The advent and diffusion of modern technologies have triggered the widespread adoption of social media by hospitals and medical clinics. Despite the increasing use of social media, its use cases in health care settings and the value proposition of each use case are yet to be explicated. To address this issue, this qualitative study explores the value of social media in health care. Relevant data were collected through semi-structured interviews with participants at 11 Australian hospitals and medical clinics. Common themes expressed by participants were identified through a thematic analysis of the transcripts. The findings revealed nine use cases of social media in health care: engaging in professional networking, harnessing patient feedback, promoting public health, educating professionals, educating patients, engaging with the public, crowdsourcing, conducting research, and patient collaboration. Furthermore, this study found that hospitals and medical clinics are not passive users of social media; rather, they make conscious decisions regarding whether, when, and how to use social media. Although social media can likely support various activities in health care settings, its value proposition for hospitals and medical clinics varies depending on the use case. Understanding such use cases and the value proposition in each use case will help more hospitals and medical clinics to incorporate social media strategically.
Description:
Recent trends in the increasing use of complementary and alternative medicine (CAM) as "holistic medicine" by patients in technologically advanced nations have prompted the need to integrate their CAM information into their Electronic health records (EHR). Studies indicate that over 70% of the public in Australia used at least one form of CAM that includes nutritional products such as vitamins, supplements, and herbal medicines, and alternate medicines such as homoeopathic, Ayurvedic and Chinese medicines. There is also a growing acceptance of CAM among healthcare providers, and patients are increasingly visiting CAM practitioners. In this paper, we argue that by unifying patients' information about their CAM history along with their EHR, the healthcare quality and accuracy of measurements could be improved, and we identify six key benefits for healthcare and CAM practitioners as well as consumers. On the other hand we also foresee certain issues, such as availability of electronic data and standardised practice of different forms of CAM, and we have unearthed six main issues that require prime attention. We discuss these issues and provide recommendations for the way to go forward in integrating automated CAM software components into EHR systems.
Description:
Recent trends in the increasing use of complementary and alternative medicine (CAM) as "holistic medicine" by patients in technologically advanced nations have prompted the need to integrate their CAM information into their Electronic health records (EHR). Studies indicate that over 70% of the public in Australia used at least one form of CAM that includes nutritional products such as vitamins, supplements, and herbal medicines, and alternate medicines such as homoeopathic, Ayurvedic and Chinese medicines. There is also a growing acceptance of CAM among healthcare providers, and patients are increasingly visiting CAM practitioners. In this paper, we argue that by unifying patients' information about their CAM history along with their EHR, the healthcare quality and accuracy of measurements could be improved, and we identify six key benefits for healthcare and CAM practitioners as well as consumers. On the other hand we also foresee certain issues, such as availability of electronic data and standardised practice of different forms of CAM, and we have unearthed six main issues that require prime attention. We discuss these issues and provide recommendations for the way to go forward in integrating automated CAM software components into EHR systems.
Description:
Studies on factors that motivate researchers conclude that financial rewards, recognition, curiosity and a desire to contribute; the so-called, Gold, Ribbons, Puzzle and Morals motivating factors, combine to explain why individuals start and continue to be researchers. Lived experience with significant, often life-changing events as a patient, carer, victim, or bystander has motivated many, directly or indirectly, including me, to become researchers. In this chapter, I draw on introspection to examine my journey through 25 years of research experience in university settings. I use concepts from dual systems theories that identify intuition and cognition as two processes that come together to explain how key events and situations in life have influenced my decisions. This illustrates how critical events have mediated the Gold, Ribbon, Puzzle and Morals factors that were motivating my research efforts.