Association of Data Mining and healthcare domain: Issues and current state of the art

Data mining has been used prosperously in the favorably perceived areas such as e- business, marketing and retail because of which it is now applicable in knowledge discovery in databases (KDD) in many industrial areas and economy. Data mining is mainly gaining its importance and usage in the areas of medicine and public health. In this paper the investigation of present methods of KDD, applying data mining methods for healthcare and public health has been discussed. The problems and difficulties related to data mining and healthcare in practice are also mentioned. In survey, the use of data mining has increased, along with examination of healthcare institutions so that the health policy prepared is the best, perceive disease causes and protect deaths in hospital and discover the dishonest insurance declaration.stabilization of continuous and fed-batch cultivation processes. In the paper are investigated Monod-Wang kinetic model and it singular Monod form. The simpler Monod and Monod-Wang models are restricted forms of Wang-Yerusalimsky model. The Wang-Yerusalimsky kinetic model could be accepted as a common model. A second order sliding mode is investigated and compared with standard sliding mode algorithms. The sliding mode control permits to solve the control problems with smaller quantity of priory information and elimination of parameters and measurements noises

Revisiting the built environment: 10 potential development changes and paradigm shifts due to COVID-19

This study explores potential development and paradigm shifts in two main sectors of construction and the built environment due to COVID-19. These development changes are discussed based on evidence from previous pandemics, current and expected impacts on both industries, and how they are likely to shape the next policy, practices, and perspectives. By assessing the primary areas of both sectors through an expert-led analysis, this study suggests 10 potential development changes that we could expect in the post-COVID time. These potential changes are discussed as possible new practices, empowered regulations, or adaptive measures; and eventually towards paradigm shifts. A total of 50 participants contributed to the selection, identification, and assessment of these potential changes. The findings from this study feed into the assessment of ongoing and forthcoming changes as a result of the current pandemic, specifically on two sectors of ‘construction’ and ‘the built environment’. These will include paradigm shifts in architecture practices, civil engineering practices, project management, and urbanism. Some of the suggestions in this study may harness shared practices, and some may simply develop into new forms of development practices in both sectors

Data Mining and Associated Analytical Tools as Decision Aids for Healthcare practitioners in Vascular Surgery

Vascular surgery is an increasingly data rich speciality. Planning treatment and assessing outcomes are highly dependent on objective assessment of number of imaging modalities including duplex ultrasound, CT scans and angiograms which are almost exclusively digitally created stored and accessed. Developments such as the national vascular registry mean that treatment outcomes are recorded scrutinised electronically. The widespread availability of data which is collected electronically and stored for future clinical use has created the opportunity to examine the efficacy of investigations and treatments in a way which has hitherto not been possible. In addition, new computational methods for data analysis have provided the opportunity for the clinicians and researchers to utilise this data to address pertinent clinical questions

Spatial Data Mining to Support Pandemic Preparedness ABSTRACT

Effective detection of and response to pandemic disease outbreaks require significant advances in data mining. Contributions to the recently held SIAM DM 2006 Workshop on Spatial Data Mining highlighted key challenges, directions, and progress in this context. We summarize here the main themes presented at the workshop as well as promising research directions for the data mining community. 1