Clostridium difficile infection incidence prediction in hospitals (CDIIPH): a predictive model based on decision tree and fuzzy techniques

Chhipi‐Shrestha, Gyan; Mori, Julie; Hewage, Kasun; Sadiq, Rehan

doi:10.1007/s00477-016-1227-5

Cited by 8 publications

(5 citation statements)

References 30 publications

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“…Zadeh (1965) introduced fuzzy sets to analyze uncertainty in decision making caused by imprecision and vagueness. The fundamentals of fuzzy sets, fuzzy number, and their mathematical operations (Chhipi-Shrestha et al, 2016) are provided in Supplemental Material C. The relevance criteria were evaluated based on a High (0.5,1,1) Variables have absolute values or one annual observation provides the data (e.g., proximity to drinking water system) for the variables. Medium (0,0.5,1) Variables have highly varying values that require a large number of observations in a year.…”

Section: Methodsmentioning

confidence: 99%

“…Zadeh (1965) introduced fuzzy sets to analyze uncertainty in decision making caused by imprecision and vagueness. The fundamentals of fuzzy sets, fuzzy number, and their mathematical operations (Chhipi-Shrestha et al, 2016) are provided in Supplemental Material C. The relevance criteria were evaluated based on a SPI has been used for urban water sustainability assessment in the region. Medium (0,0.5,1) SPI has been used for urban water sustainability assessment outside the region.…”

Section: Methodsmentioning

confidence: 99%

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Selecting Sustainability Indicators for Small to Medium Sized Urban Water Systems Using Fuzzy‐ELECTRE

Chhipi‐Shrestha

Hewage

Sadiq

2017

Water Environment Research

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This paper investigates a novel simulation-optimization (S-O) framework for identifying optimal treatment levels and treatment processes for multiple wastewater dischargers to rivers. A commonly used water quality simulation model, Qual2K, was linked to a Genetic Algorithm optimization model for exploration of relevant fuzzy objective-function formulations for addressing imprecision and conflicting goals of pollution control agencies and various dischargers. Results showed a dynamic flow dependence of optimal wastewater loading with good convergence to near global optimum. Explicit considerations of real-world technological limitations, which were developed here in a new S-O framework, led to better compromise solutions between conflicting goals than those identified within traditional S-O frameworks. The newly developed framework, in addition to being more technologically realistic, is also less complicated and converges on solutions more rapidly than traditional frameworks. This technique marks a significant step forward for development of holistic, riverscape-based approaches that balance the conflicting needs of the stakeholders.

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Section: Methodsmentioning

confidence: 99%

“…Zadeh (1965) introduced fuzzy sets to analyze uncertainty in decision making caused by imprecision and vagueness. The fundamentals of fuzzy sets, fuzzy number, and their mathematical operations (Chhipi-Shrestha et al, 2016) are provided in Supplemental Material C. The relevance criteria were evaluated based on a SPI has been used for urban water sustainability assessment in the region. Medium (0,0.5,1) SPI has been used for urban water sustainability assessment outside the region.…”

Section: Methodsmentioning

confidence: 99%

Selecting Sustainability Indicators for Small to Medium Sized Urban Water Systems Using Fuzzy‐ELECTRE

Chhipi‐Shrestha

Hewage

Sadiq

2017

Water Environment Research

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“…Evidence theory was developed by Shafer and was firstly proposed by Dempster [ 30 ], thus it is also called D–S evidence theory. Recently, theoretical research on evidence theory has played a very important role in many applications such as decision-making [ 31 , 32 , 33 , 34 ], complex networks [ 35 , 36 ], fault diagnosis [ 37 , 38 , 39 , 40 , 41 ], classification [ 42 , 43 ] and so on [ 44 , 45 , 46 , 47 ].…”

Section: Preliminariesmentioning

confidence: 99%

An Intuitionistic Evidential Method for Weight Determination in FMEA Based on Belief Entropy

Liu

Xiao

2019

Entropy

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Failure Mode and Effects Analysis (FMEA) has been regarded as an effective analysis approach to identify and rank the potential failure modes in many applications. However, how to determine the weights of team members appropriately, with the impact factor of domain experts’ uncertainty in decision-making of FMEA, is still an open issue. In this paper, a new method to determine the weights of team members, which combines evidence theory, intuitionistic fuzzy sets (IFSs) and belief entropy, is proposed to analyze the failure modes. One of the advantages of the presented model is that the uncertainty of experts in the decision-making process is taken into consideration. The proposed method is data driven with objective and reasonable properties, which considers the risk of weights more completely. A numerical example is shown to illustrate the feasibility and availability of the proposed method.

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“…The risk factors identified for CDI are the use of antibiotics, stomach acid-suppressing medications, primarily proton-pump inhibitors (PPI), advanced age (above 64 years), prior hospitalization, exposure to CDI patients, weak health condition, among others (2).…”

Section: Introductionmentioning

confidence: 99%

Prediction of Clostridium difficile infection in patients with polymerase chain reaction using a classification and regression tree

Martínez-Ruíz

Parra-Lara

Rosso

2020

Preprint

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BackgroundClostridium difficile infection (CDI) is commonly diagnosed with the polymerase chain reaction (PCR), but this test finds a high percentage of false positives, so their use and interpretation in CDI is a challenge in the clinical practice. That is why it is necessary to define an algorithm to optimize the use of PCR that considers clinical characteristics to classify patients with diarrhea as CDI or without CDI. ObjectiveTo identify a predictive algorithm with the clinical features that best classify patients with CDI vs. without CDI, to help physicians in making decisions to request PCR. Materials and methodsA case-control study was conducted at Fundación Valle del Lili. The population was inpatients between 2012 and 2016, with 18 or more years, and diarrhea, abdominal pain, or other nonspecific gastrointestinal symptoms who underwent PCR. Cases were defined as patients with positive PCR for C. difficile and as controls patients with negative PCR for C. difficile. Predictive algorithms to classify patients was constructed using a classification tree, classification and regression tree (CART). ResultsA total of 149 patients were included (48 cases with positive PCR and 99 controls with negative PCR). The CART has a high capacity to classify patients with a negative PCR correctly. It includes variables about the history of antibiotics use, the use of proton-pump inhibitor, the use of ranitidine, and the use of antifungal drugs. The CART showed sensitivity 64.6%, specificity 85.8%, positive predictive value 68.8%, negative predictive value 83.3%. and AUC 79.7%.DiscussionCART had good specificity and a high negative predictive value; it could be considered as an algorithm to identify conditions that indicate when it is not necessary to perform a PCR test in a patient symptom of CDI.

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Clostridium difficile infection incidence prediction in hospitals (CDIIPH): a predictive model based on decision tree and fuzzy techniques

Cited by 8 publications

References 30 publications

Selecting Sustainability Indicators for Small to Medium Sized Urban Water Systems Using Fuzzy‐ELECTRE

Selecting Sustainability Indicators for Small to Medium Sized Urban Water Systems Using Fuzzy‐ELECTRE

An Intuitionistic Evidential Method for Weight Determination in FMEA Based on Belief Entropy

Prediction of Clostridium difficile infection in patients with polymerase chain reaction using a classification and regression tree

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