14 research outputs found

    KACST Arabic Text Classification Project: Overview and Preliminary Results

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    Electronically formatted Arabic free-texts can be found in abundance these days on the World Wide Web, often linked to commercial enterprises and/or government organizations. Vast tracts of knowledge and relations lie hidden within these texts, knowledge that can be exploited once the correct intelligent tools have been identified and applied. For example, text mining may help with text classification and categorization. Text classification aims to automatically assign text to a predefined category based on identifiable linguistic features. Such a process has different useful applications including, but not restricted to, E-Mail spam detection, web pages content filtering, and automatic message routing. In this paper an overview of King Abdulaziz City for Science and Technology (KACST) Arabic Text Classification Project will be illustrated along with some preliminary results. This project will contribute to the better understanding and elaboration of Arabic text classification techniques

    Prevalence and risk factors of dry eye disease among adults in Saudi Arabia

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    Background: Environmental and epidemiological factors increase the risk of dry eye in Saudi Arabia, but most studies have limited generalizability. Objective: To determine the prevalence of dry eye disease (DED) among adults across Saudi Arabia and the associated risk factors. The secondary objective was to estimate the economic burden of DED by calculating lubricant usage and its annual costs. Methods: This cross-sectional study invited adults from across Saudi Arabia to complete a questionnaire that collected data regarding demographics, symptoms related to DED, previous diagnosis of DED, use of contact lenses, and use of eye lubricants. Results: A total of 2042 responses were received, of which 784 (38.4%) respondents had previously been diagnosed with DED and 752 (36.8%) were symptomatic but undiagnosed. Between the DED diagnosed and symptomatic-undiagnosed groups, a significant difference was found in terms of age (P < 0.001), gender (P = 0.002), presence of diabetes mellitus (P = 0.004), smoking status (P = 0.007), duration of electronic screen use (P = 0.05), number of ocular complaints (P < 0.001), and frequency of lubricants use (P < 0.001). Between the DED-diagnosed and non-DED groups, significant differences were found in terms of age (P < 0.001), gender (P < 0.001), presence of diabetes mellitus (P = 0.001), allergy (P = 0.001), autoimmune disease (P = 0.005), smoking status (P < 0.001), and history of refractive surgery (P < 0.001). The mean estimated annual cost of using lubricating agents was SAR 328.2 ± 210.3 (USD 87.5 ± 56.1), and this was significantly higher in the diagnosed group (P = 0.01) than the symptomatic-undiagnosed group. Conclusions: The prevalence of DED is high among adults in Saudi Arabia. High-risk population include elderly, female, and using electronic screens for >2 hours/day

    ASCHOPLEX:A generalizable approach for the automatic segmentation of choroid plexus

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    Background: The Choroid Plexus (ChP) plays a vital role in brain homeostasis, serving as part of the Blood-Cerebrospinal Fluid Barrier, contributing to brain clearance pathways and being the main source of cerebrospinal fluid. Since the involvement of ChP in neurological and psychiatric disorders is not entirely established and currently under investigation, accurate and reproducible segmentation of this brain structure on large cohorts remains challenging. This paper presents ASCHOPLEX, a deep-learning tool for the automated segmentation of human ChP from structural MRI data that integrates existing software architectures like 3D UNet, UNETR, and DynUNet to deliver accurate ChP volume estimates. Methods: Here we trained ASCHOPLEX on 128 T1-w MRI images comprising both controls and patients with Multiple Sclerosis. ASCHOPLEX's performances were evaluated using traditional segmentation metrics; manual segmentation by experts served as ground truth. To overcome the generalizability problem that affects data-driven approaches, an additional fine-tuning procedure (ASCHOPLEXtune) was implemented on 77 T1-w PET/MRI images of both controls and depressed patients. Results: ASCHOPLEX showed superior performance compared to commonly used methods like FreeSurfer and Gaussian Mixture Model both in terms of Dice Coefficient (ASCHOPLEX 0.80, ASCHOPLEXtune 0.78) and estimated ChP volume error (ASCHOPLEX 9.22%, ASCHOPLEXtune 9.23%). Conclusion: These results highlight the high accuracy, reliability, and reproducibility of ASCHOPLEX ChP segmentations.</p

    Business at the margins? Business interests in edge urban politics

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    The issue of the organization, role and influence of business interests in urban politics at the edge of major cities is one that is overdue for investigation. This article provides an initial and empirically oriented investigation of the organization, role and influence of business interests in edge urban politics in Europe. We present findings from five members of a European network of self-styled 'edge cities'. Following the now extensive debate in academic literature regarding the applicability of US concepts such as growth machines and urban regimes to the European setting, we draw attention to a diversity of business involvement in urban politics at the edge of Europe's capital cities. This diversity does include instances that, despite the very different 'macro-necessities' structuring edge urban politics in Europe, approximate to these concepts. Moreover, the diversity apparent in edge urban business politics raises several important questions for future research on urban governance. Namely, the complex connection between the local dependence of business and the organization of its interests; the 'jumping of scales' by locally dependent edge urban actors, and the sometimes neglected articulation of business interests with party political organization
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