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Data Cleaning Utilizing Ontology Tool
Jing Ting Wong,Jer Lang Hong 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.7
Recent advancement in Internet Technologies has made web browsing increasingly easy and user friendly. From the traditional method of desktop web browsing and the birth of dial up modem connection, users nowadays are able to enjoy a fast and reliable web browsing via high speed wireless Internet connection and portable mobile devices. Browsing a web has become much easier with the state of the art search engines such as Google, which provide much functionalities which could make browsing easier such as improved crawler, easy to use search interface, web personlization, Web 3.0 support and integration and many more. In order to build a robust and reliable search engine, the developer needs to integrate all the data and present them in a meaningful format for user’s viewing convenience. Integrating these data is a tedious task as data usually occur in numerous format, and layout. Furthermore, web developers usually present the data content in various languages of their choice, which made the processing of these data increasingly difficult. There is also no standard convention to represent the data format and even a standardize rule to process this data has not been developed. To resolve this issue, researchers develop data extractor which could effectively extract data from web sources, tabulate them, and used it for further processing. However, not all data are correctly extracted, they may either missed certain valuable information or contain additional unnecessary information. In the case of unnecessary information, researchers use a cleaning method to remove them such that the data extracted are free of errors. Removing these data is important as unnecessary information may affect the accuracy of subsequent extractor tools, hence may eventually prevent the tool from performing its task efficiently. In this research proposal, we embark on a data cleaning tool to clean data using ontology tools. Experimental results show that our tool is highly efficient in data cleaning and is able to outperform existing state of the art tools.
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Wong Joanna K. L.,Ke Yuhe,Ong Yi Jing,Li HuiHua,Wong Ting Hway,Abdullah Hairil Rizal 대한마취통증의학회 2022 Korean Journal of Anesthesiology Vol.75 No.1
Background: Diabetes is a risk factor for postoperative complications. Previous meta-analyses have shown that elevated glycated hemoglobin (HbA1c) levels are associated with postoperative complications in various surgical populations. However, this is the first meta-analysis to investigate the association between preoperative HbA1c levels and postoperative complications in patients undergoing elective major abdominal surgery.Methods: PRISMA guidelines were adhered to for this study. Six databases were searched up to April 1, 2020. Primary studies investigating the effect of HbA1c levels on postoperative complications after elective major abdominal surgery were included. Risk of bias and quality of evidence assessments were performed. Data were pooled using a random effects model. Meta-regression was performed to evaluate different HbA1c cut-off values. Results: Twelve observational studies (25,036 patients) were included. Most studies received a ‘good’ and ‘moderate quality’ score using the NOS and GRADE, respectively. Patients with a high HbA1c had a greater risk of anastomotic leaks (odds ratio [OR]: 2.80, 95% CI [1.63, 4.83], P < 0.001), wound infections (OR: 1.21, 95% CI [1.08, 1.36], P = 0.001), major complications defined as Clavien-Dindo [CD] 3–5 (OR: 2.16, 95% CI [1.54, 3.01], P < 0.001), and overall complications defined as CD 1–5 (OR: 2.12, 95% CI [1.48, 3.04], P < 0.001).Conclusions: An HbA1c between 6% and 7% is associated with higher risks of anastomotic leaks, wound infections, major complications, and overall postoperative complications. Therefore, guidelines with an HbA1c threshold > 7% may be putting pre-optimized patients at risk. Future randomized controlled trials are needed to explore causation before policy changes are made.
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Liu Gabriel Ka-Po,Tan Jiong Hao,Kong Jun Cheong,Tan Yong Hao Joel,Kumar Nishant,Liang Shen,Shawn Seah Jing Sheng,Ting Chiu Shi,Lim Lau Leok,Dennis Hey Hwee Weng,Kumar Naresh,Thambiah Joseph,Wong Hee-K 대한척추외과학회 2022 Asian Spine Journal Vol.16 No.6
Study Design: A retrospective cohort study of patients with surgically treated thoracolumbar fractures.Purpose: This study aimed to describe the incidence of adverse events (AEs) after surgical stabilization of thoracolumbar spine injuries and to identify predictive factors for the occurrence of AEs. Overview of Literature: Thoracolumbar spine fractures are frequently present in patients with blunt trauma and are associated with significant morbidity. AEs can occur due to the initial spinal injury or secondary to surgical treatment. There is a lack of emphasis in the literature on the AEs that can occur after operative management of thoracolumbar fractures.Methods: We performed a retrospective review of 199 patients with surgically treated thoracolumbar fractures operated between January 2007 and January 2018. The potential risk factors for the development of AEs as well as the development of common complications were evaluated by univariate analysis, and a multivariate logistic regression analysis was performed to identify independent risk factors predictive of the above.Results: The overall rate of AEs was 46.7%; 83 patients (41.7%) had nonsurgical AEs, whereas 24 (12.1%) had surgical adverse events. The most common AEs were urinary tract infections in 43 patients (21.6%), and hospital-acquired pneumonia in 21 patients (10.6%). On multivariate logistic regression, a Thoracolumbar Injury Classification and Severity (TLICS) score of 8–10 (odds ratio [OR], 6.39; 95% confidence interval [CI], 2.33–17.51), the presence of polytrauma (OR, 2.64; 95% CI, 1.17–5.99), and undergoing open surgery (OR, 2.31; 95% CI, 1.09–4.88) were significant risk factors for AEs. The absence of neurological deficit was associated with a lower rate of AEs (OR, 0.47; 95% CI, 0.31–0.70).Conclusions: This study suggests the presence of polytrauma, preoperative American Spinal Injury Association score, and TLICS score are predictive of AEs in patients with surgically treated thoracolumbar fractures. The results might also suggest a role for minimally invasive surgical methods in reducing AEs in these patients.
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