1,720,996 research outputs found
A case of brain abscess due to parvimonas micra in a healthy child without dental disease
Full text linkParvimonas micra is a non-spore-forming anaerobic gram-positive coccus and a known commensal of the skin, gums, vagina, and gastrointestinal tract. It is rarely associated with severe infections, which typically follow invasive procedures such as dental treatment. We describe a case of a brain abscess caused by P. micra in an immunocompetent 11-year-old boy without periodontal disease. He presented with a 7-day history of headaches and vomiting, and complained of diplopia that began on the day of presentation. He did not have any recent dental treatment or specific past medical history. A brain abscess in the left frontoparietal lobe was noted on brain magnetic resonance imaging. P. micra was cultured from brain abscess aspirate. He was successfully treated with surgical drainage and combined antibiotic therapy with ceftriaxone and metronidazole for 6 weeks. Copyright © 2020 The Korean Society of Pediatric Infectious Diseases
The collaborative filtering recommendation based on SOM cluster-indexing CBR
No full textCollaborative filtering (CF) recommendation is a knowledge sharing technology for distribution of opinions and facilitating contacts in network society between people with similar interests. The main concerns of the CIF algorithm are about prediction accuracy, speed of response time, problem of data sparsity, and scalability. In general, the efforts of improving prediction algorithms and lessening response time are decoupled. We propose a three-step CIF recommendation model, which is composed of profiling, inferring, and predicting steps while considering prediction accuracy and computing speed simultaneously. This model combines a CF algorithm with two machine learning processes, Self-Organizing Map (SOM) and Case Based Reasoning (CBR) by changing an unsupervized clustering problem into a supervized user preference reasoning problem, which is a novel approach for the CF recommendation field. This paper demonstrates the utility of the CF recommendation based on SOM cluster-indexing CBR with validation against control algorithms through an open dataset of user preference. (C) 2003 Elsevier Ltd. All rights reserved
Prognostic personal credit risk model considering censored information
No full textCredit scoring is one of the most successful applications of quantitative analysis that helps organizations decide whether or not to grant credit to consumers who apply to them. However, standard credit risk models based on binary classifying approaches appear to have missed several important time-varying factors and censoring information. This paper looks at the extensions of the survival analysis model to analyze personal credit risk. Survival analysis has mainly been used in the clinical domain, which can handle the above issues. This paper investigates the ability of the survival-based approach to predict the probability of personal default. The proposed method can give a prediction of `time' as well as `probability' of personal default. We develop a survival-based credit risk model and assess the relative importance of different variables in predicting default. Standard binary classifying models are also developed for assessing a new way in the context of classifying power. These models are applied to personal credit card accounts dataset. According to the experiment results, survival-based credit risk modeling is a more useful approach for classifying risky customers than others. The survival-based approach is a useful alternative and a complement in view of personal credit risk. (c) 2005 Elsevier Ltd. All rights reserved
The priority factor model for customer relationship management system success
No full textAs the market competition becomes keen, constructing a customer relationship management system is coming to the front for winning over new customers, developing service and products for customer satisfaction and retaining existing customers. However, decisions for CRM implementation have been hampered by inconsistency between information technology and marketing strategies, and the lack of conceptual bases necessary to develop the success measures. Using a structural equation analysis, this study explores the CRM system success model that consists of CRM initiatives: process fit, customer information quality, and system support; intrinsic success: efficiency and customer satisfaction; and extrinsic success: profitability. These constructs underlie much of the existing literature on information system success and customer satisfaction perspectives. We found the empirical support for CRM implementation decision-making from 253 respondents of 14 companies which have implemented the CRM system. These findings should be of great interest to both researchers and practitioners. (c) 2005 Elsevier Ltd. All rights reserved
Importance of Sufficient Petrosectomy in an Anterior Petrosal Approach: Relightening of the Kawase Pyramid
No full textBackground: In 1985, Kawase published an anterior petrosal approach to expose the posterior cranial fossa and to minimize retraction of the temporal lobe. However, some neurosurgeons still have difficulty with removing tumors through an anterior petrosal approach because a complete understanding of the Kawase pyramid has not been achieved. We hypothesized that if anterior petrosectomy were performed with three-dimensional understanding of the Kawase pyramid, it would have a positive effect on extent of tumor resection. Methods: We performed a retrospective study of patients who underwent surgical treatment for meningioma through an anterior petrosal approach. Patients were divided into total resection and subtotal resection groups, and statistical differences between the groups were analyzed. To identify factors predictive of complete tumor removal, univariable and multivariable logistic regression analyses were performed. Results: Width and height of the drilled internal auditory canal of the total resection group were significantly larger than those of the subtotal resection group (P = 0.001, P = 0.033). The operative angle of the total resection group was significantly larger than that of the subtotal resection group (P < 0.001). Regression analyses showed only drilled internal auditory canal width to be predictive of complete tumor removal, increasing the likelihood of complete tumor removal by 2.778-fold with an increase in drilled internal auditory canal width by 1 mm (P = 0.023). Conclusions: Insufficient petrosectomy during an anterior petrosal approach adversely affects the extent of tumor resection. Furthering three-dimensional understanding of the Kawase pyramid could aid in complete tumor resection and better outcomes without causing damage to the surrounding organs
Incidental Detection of Meningioma on 18F-Flutemetamol PET
No full textMeningioma is typically a benign tumor that may incidentally be found on imaging. This case demonstrates the utility of 18 F-flutemetamol (FMM) PET/CT in an 80-year-old woman evaluated for memory decline. Although the scan was performed for dementia assessment, it revealed an incidental mass in the frontal region. Early-phase PET showed relatively low uptake, while delayed-phase imaging displayed intense uptake of 18 F-FMM. Magnetic resonance imaging and surgical pathology confirmed the lesion as a meningioma. This report may aid in interpreting incidental mass lesions on 18 F-FMM PET, providing a reference for physicians who may encounter similar findings
Association between Levetiracetam Use and Survival in Patients with Glioblastoma: A Nationwide Population-Based Study
No full textPURPOSE: This study aimed to investigate whether levetiracetam (LEV), the most used antiepileptic drug, influences survival in patients with glioblastoma (GBM), using a national database. MATERIALS AND METHODS: This study used data from the Korea Health Insurance Review and Assessment database. Patients diagnosed with GBM between 2007-2018 treated with standard therapy were included. The study population was divided into long-term (>/= 60 days) and short-term (< 30 days) LEV groups. A separate long-term valproic acid (VPA) group (>/= 60 days) was identified for comparison. Demographics, disease characteristics, and treatment parameters were collected. Kaplan-Meier method and Cox regression were used to compare survival outcomes between the groups. RESULTS: Overall, 2,971 patients were included, with 1,319 and 1,652 in the short-term and long-term LEV groups, respectively. The median overall survival (OS) for the entire population was 19.15 months post-surgery. Kaplan-Meier analysis revealed a significantly longer median OS in the long-term LEV group versus the short-term LEV group. After adjusting for confounders, Cox proportional hazard analysis revealed an association of long-term LEV use with improved survival, which was also observed in a subgroup analysis of patients without preoperative seizure history. The long-term LEV group demonstrated longer median OS, compared with the long-term VPA group. CONCLUSION: Our nationwide population-based study found an association between long-term LEV use and improved survival in patients with GBM, regardless of preoperative seizure history. Prospective studies are needed to validate these findings and investigate the potential impact of LEV on the survival outcomes of patients with GBM
Bevacizumab Alone Versus Bevacizumab Plus Irinotecan in Patients With Recurrent Glioblastoma: A Nationwide Population-Based Study
Full text linkBackground: For treating recurrent glioblastoma, for which there is no established treatment, the antiangiogenic antibody, bevacizumab, is used alone or with irinotecan. This study was aimed at comparing the survival of patients with recurrent glioblastoma receiving bevacizumab monotherapy and those receiving bevacizumab plus irinotecan combination therapy (B+I) by using a nationwide population-based dataset. Methods: Patients matching the International Classification of Diseases code C71.x were screened from the Health Insurance Review and Assessment Service database. From January 2008 to November 2021, patients who underwent surgery or biopsy and subsequent standard concurrent chemoradiation with temozolomide were included. Among them, those who received bevacizumab monotherapy or B+I were selected. Demographic characteristics, inpatient stay, prescription frequency, survival outcomes, and steroid prescription duration were compared between these two groups. Results: Eight hundred and forty-six patients who underwent surgery or biopsy and received concurrent chemoradiotherapy with temozolomide were included. Of these, 450 and 396 received bevacizumab monotherapy and B+I, respectively. The corresponding median overall survival from the initial surgery was 22.60 months (95% confidence interval [CI], 20.50–24.21) and 20.44 months (95% CI, 18.55–22.60; P = 0.508, log-rank test). The B+I group had significantly more bevacizumab prescriptions (median 5 times; BEV group: median 3 times). Cox analysis, based on the postsurgery period, revealed that male sex (hazard ratio [HR], 1.28; P = 0.002), older age (HR, 1.01; P = 0.042), and undergoing biopsy instead of surgery (HR, 1.79; P < 0.0001) were significantly associated with decreased survival. Fewer radiotherapy cycles correlated with improved survival outcomes (HR, 0.63; P = 0.001). Cox analysis, conducted from the start of chemotherapy including bevacizumab, showed that male sex was the only variable significantly associated with decreased survival (HR, 1.18; P = 0.044). Conclusion: We found no significant difference in overall survival between the bevacizumab monotherapy and B+I groups. Considering the additional potential toxicity associated with irinotecan, bevacizumab monotherapy could be a suitable treatment option for treating recurrent glioblastoma
Convolutional neural network-based classification of craniosynostosis and suture lines from multi-view cranial X-rays
Full text linkEarly and precise diagnosis of craniosynostosis (CSO), which involves premature fusion of cranial sutures in infants, is crucial for effective treatment. Although computed topography offers detailed imaging, its high radiation poses risks, especially to children. Therefore, we propose a deep-learning model for CSO and suture-line classification using 2D cranial X-rays that minimises radiation-exposure risks and offers reliable diagnoses. We used data comprising 1,047 normal and 277 CSO cases from 2006 to 2023. Our approach integrates X-ray-marker removal, head-pose standardisation, skull-cropping, and fine-tuning modules for CSO and suture-line classification using convolution neural networks (CNNs). It enhances the diagnostic accuracy and efficiency of identifying CSO from X-ray images, offering a promising alternative to traditional methods. Four CNN backbones exhibited robust performance, with F1-scores exceeding 0.96 and sensitivity and specificity exceeding 0.9, proving the potential for clinical applications. Additionally, preprocessing strategies further enhanced the accuracy, demonstrating the highest F1-scores, precision, and specificity. A qualitative analysis using gradient-weighted class activation mapping illustrated the focal points of the models. Furthermore, the suture-line classification model distinguishes five suture lines with an accuracy of > 0.9. Thus, the proposed approach can significantly reduce the time and labour required for CSO diagnosis, streamlining its management in clinical settings
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