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Gyan?Chhipi-ShresthaEmail author Julie?Mori Kasun?Hewage Rehan?Sadiq 《Stochastic Environmental Research and Risk Assessment (SERRA)》2017,31(2):417-430
Several risk factors associated with the increased likelihood of healthcare-associated Clostridium difficile infection (CDI) have been identified in the literature. These risk factors are mainly related to age, previous CDI, antimicrobial exposure, and prior hospitalization. No model is available in the published literature that can be used to predict the CDI incidence using healthcare administration data. However, the administrative data can be imprecise and may challenge the building of classical statistical models. Fuzzy set theory can deal with the imprecision inherent in such data. This research aimed to develop a model based on deterministic and fuzzy mathematical techniques for the prediction of hospital-associated CDI by using the explanatory variables controllable by hospitals and health authority administration. Retrospective data on CDI incidence and other administrative data obtained from 22 hospitals within a regional health authority in British Columbia were used to develop a decision tree (deterministic technique based) and a fuzzy synthetic evaluation model (fuzzy technique based). The decision tree model had a higher prediction accuracy than that of the fuzzy based model. However, among the common results predicted by two models, 72 % were correct. Therefore, this relationship was used to combine their results to increase the precision and the strength of evidence of the prediction. These models were further used to develop an Excel-based tool called C. difficile Infection Incidence Prediction in Hospitals (CDIIPH). The tool can be utilized by health authorities and hospitals to predict the magnitude of CDI incidence in the following quarter. 相似文献
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Bingyi Kang Gyan Chhipi-Shrestha Yong Deng Kasun Hewage Rehan Sadiq 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(6):1743-1758
Clostridium difficile infection is one of the major patient safety concerns in hospitals worldwide. Clostridium difficile infection can have high economic burden to patients, hospitals, and government. Limited work has been done in the area of predictive modeling. In this article, A new predictive model based on Gaussian mixture model and Dempster–Shafter theory is proposed to predict Clostridium difficile infection incidence in hospitals. First, the Gaussian mixture model and expectation–maximization algorithms are used to generate explicit probability criteria of risk factors based on the given data. Second, Dempster–Shafter theory is used to predict the Clostridium difficile infection incidence based on the generated probability criteria that have different beliefs attributing to their different credits. The main procedure includes (1) generate the probability criteria model using Gaussian mixture model and expectation–maximization algorithm; (2) determine the credit of the probability criteria; (3) generate the basic probability assignment; (4) discount the evidences; (5) aggregate the evidences using Dempster combining rule; (6) predict Clostridium difficile infection incidence using pignistic probability transformation. Results show that the model has a higher accuracy than an existing model. The proposed model can generate the criteria ratings of risk factors automatically, which would potentially prevent the imprecision caused by the subjective judgement of experts. The proposed model can assist risk managers and hospital administrators in the prediction and control of Clostridium difficile infection incidence with optimizing their resources. 相似文献
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Kasun Gayantha Joyanto Routh Krishnamurthy Anupama Jean Lazar Srinivasan Prasad Rohana Chandrajith Patrick Roberts Gerd Gleixner 《第四纪科学杂志》2020,35(4):514-525
The catastrophic impact and unpredictability of the Indian Ocean Monsoon (IOM) over South Asia are evident from devastating floods, mudslides and droughts in one of the most densely populated regions of the globe. However, our understanding as to how the IOM has varied in the past, as well as its impact on local environments, remains limited. This is particularly the case for Sri Lanka, where erosional landscapes have limited the availability of well-stratified, high-resolution terrestrial archives. Here, we present novel data from an undisturbed sediment core retrieved from the coastal Bolgoda Lake. This includes the presentation of a revised Late Holocene age model as well as an innovative combination of pollen, source-specific biomarkers, and compound-specific stable carbon isotopes of n-alkanes to reconstruct the shifts in precipitation, salinity and vegetation cover. Our record documents variable climate between 3000 years and the present, with arid conditions c. 2334 and 2067 cal a bp. This extreme dry period was preceded and followed by more wet conditions. The high-resolution palaeoenvironmental reconstruction fills a major gap in our knowledge on the ramifications of IOM shifts across South Asia and provides insights during a time of major redistribution of dense human settlements across Sri Lanka. 相似文献
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Natural Resources Research - Blasting outcomes have significant impacts on downstream mining operations such as loading, hauling, crushing, milling, and mineral processing. An ideal blasting plan... 相似文献
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Qian?PanEmail author Gyan?Chhipi-Shrestha Deyun?Zhou Kun?Zhang Kasun?Hewage Rehan?Sadiq 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(4):1099-1111
Water reuse is a viable option to increase urban water supply, especially under new realities of climate change and increasing anthropogenic activities. A sustainable water reuse application should be cost-effective and have acceptable health risk to consumers. Water reuse application evaluation is complex because data acquisitions are usually associated with the problems of uncertainty, hesitancy, and parameterization. In this paper, a generalized intuitionistic fuzzy soft set (GIFSS)-based decision support framework is proposed to provide an effective approach to describe uncertainty and hesitancy in an intuitionistic fuzzy number. In addition, the modified measures of comparison and similarity are proposed to compare water reuse applications. Then, the proposed framework is applied to the City of Penticton (British Columbia, Canada) to evaluate seven water reuse applications. The evaluation results show that the applications of garden flower watering and public parks watering are the most preferred alternatives, which are consistent with the existing practice in the city. Furthermore, the results are highly affected by the generalized parameter and the weights of evaluation criteria. Both the comparison measure-based and similarity measure-based evaluations within the same GIFSS-based framework produce consistent results, indicating an applicable and efficient methodology. 相似文献
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