Towards intelligent diabetes knowledge management and knowledge discovery : a data mining approach

Self-monitoring and self-management play an increasingly vital role in the management of prevalent diseases afflicting millions of people worldwide. Conditions such as cardiovascular disease or diabetes mellitus can be managed with pharmaceuticals. However, lifestyle factors and behaviour modifications also play a crucial part in controlling outcomes. If carried out effectively, self-monitoring and management techniques can benefit the patient from a health point of view, empowering them to take control of their disease, and also support the health sector economically. A recent report showed that almost four fifths of the NHS diabetes budget was spent on managing preventable complications. Although applicable to any medical conditions with lifestyle control elements, this thesis will be using diabetes mellitus as a recurring theme to highlight research conducted. Diabetes is a rapidly growing epidemic disease with global implications impacting humans socially and economically. By 2025 it is estimated that five million people in the UK will be diagnosed with diabetes., This research will therefore, be relevant for a large proportion of the population.Knowledge Management (KM) has demonstrated to be a valuable approach to sharing knowledge and providing users with the information necessary to help self-manage their symptoms. Although, KM has not yet been applied sufficiently to support the growing number of diabetics in the UK. In this thesis, KM is merged with Knowledge Discovery (KD) to combat that and address the specific needs of the diabetic population. The integrated framework is implemented using data mining techniques within the proposed e-Toolkit to elicit useful knowledge encountered by patients regardless of their disease, such as adverse drug reactions. The knowledge is then disseminated through the proposed modified SECI Model for knowledge creation via the e-Toolkit.The second part of this research investigates which patient data is necessary to disseminate to healthcare professionals. This help to bridge any communications gap that may exist between patients and health care professionals. In theory, the e-toolkit will provide patients with one place to record every important health factor, whilst simultaneously allowing the medical team with real-time monitoring. Thus, enabling doctors and patients to work together to find effective ways to reduce the damaging effects of this disease, including determining the common side effects through medication reviews. Keywords: Diabetes, Knowledge Management, Knowledge Discovery, British National Health Service Web System, Doctor, Patient, Data Mining

Development of a prototype for multidimensional performance management in software engineering

Managing performance is an important, and difficult, topic, and tools are needed to help organizations manage their performance. Understanding, and improving performance is an important problem. Performance management has become more and more important for organizations, and managers are always on the lookout for better solutions to manage performance within their organizations. One of the most important consequences of not having a Performance Management Framework (PMF) in place is the difficulty of differentiating organizational success from failure over time. Performance Management Frameworks have become important to organizations that need to plan, monitor, control, and improve their decisions. Use of a PMF can show an organization how it is performing and indicate whether or not an organization is going in the right direction to achieve its objectives. Over the years, several frameworks have been developed to address the management of organizational assets, both tangible and intangible. Performance measurement has always mostly been focused on the economic viewpoint. The framework developed by Kaplan and Norton adds three other viewpoints to this, and this addition represents a significant improvement to PMFs. The PMFs currently proposed do not meet the analytical requirements of software engineering management when various viewpoints must be taken into account concurrently. This difficulty is compounded by the fact that the underlying quantitative data are multidimensional, and so the usual two- and three-dimensional approaches to visualization are generally not sufficient to represent such models. Organizations vary considerably in the wide variety of viewpoints that influence their performance, and every organization has their own viewpoints that they want to manage, and which must be represented in a consolidated manner. The purpose of this thesis is to develop a prototype for managing multidimensional performance in software engineering. The thesis begins by defining the important terms or key concepts used in the research: software, performance, management, model, multidimensional, development, engineering, and prototype, and the various associations of these terms. This is followed by a review of the multidimensional PMFs that are specific to software engineering and the generic multidimensional performance models that are available to management. A framework for managing performance in software engineering in four phases: design, implementation, use of the framework, and performance improvement is then presented. Based on this framework, a prototype tool is developed. The prototype notably includes visual analytical tools to manage, interpret, and understand the results in a consolidated manner, while at the same time keeping track of the values of the individual dimensions of performance. The repository of software project data made available by the International Software Benchmarking Standard Group (ISBSG) is integrated into and used by the prototype as well