University of Lincoln

About: University of Lincoln is a education organization based out in Lincoln, Lincolnshire, United Kingdom. It is known for research contribution in the topics: Population & Context (language use). The organization has 2341 authors who have published 7025 publications receiving 124797 citations.

The incidence rate of female breast cancer in Saudi Arabia: an observational descriptive epidemiological analysis of data from Saudi Cancer Registry 2001-2008.

Abstract: Background: This study presents descriptive epidemiological data related to breast cancer cases diagnosed from 2001 to 2008 among Saudi women, including the frequency and percentage of cases, the crude incidence rate (CIR), and the age-standardized incidence rate (ASIR), adjusted by the region and year of diagnosis. Methods: This is a retrospective descriptive epidemiological study of all Saudi female breast cancer cases from 2001 to 2008. The statistical analyses were conducted using descriptive statistics, a linear regression model, and analysis of variance with the Statistical Package for the Social Sciences version 20 (IBM Corporation, Armonk, NY, USA). Results: A total of 6,922 female breast cancer cases were recorded in the Saudi Cancer Registry from 2001 to 2008. The highest overall percentages (38.6% and 31.2%) of female breast cancer cases were documented in women who were 30–44 and 45–59 years of age, respectively. The eastern region of Saudi Arabia had the highest overall ASIR, at 26.6 per 100,000 women, followed by Riyadh at 20.5 and Makkah at 19.4. Jazan, Baha, and Asir had the lowest average ASIRs, at 4.8, 6.1, and 7.3 per 100,000 women, respectively. The region of Jouf (24.2%; CIR 11.2, ASIR 17.2) had the highest changes in CIR and ASIR from 2001 to 2008. While Qassim, Jazan and Tabuk recorded down-trending rates with negative values. Conclusion: There was a significant increase in the CIRs and ASIRs for female breast cancer between 2001 and 2008. The majority of breast cancer cases occurred among younger women. The region of Jouf had the greatest significant differences of CIR and ASIR during 2001 to 2008. Jazan, Baha, and Najran had the lowest average CIRs and ASIRs of female breast cancer, whereas the linear trend upward is a concern in certain regions, such as the eastern region, Makkah, and Riyadh. However, further analytical epidemiological research is needed to identify the potential risk factors involved in the increase in the prevalence of breast cancer among Saudi women.

Transparent Adaptation in Deep Medical Image Diagnosis

Abstract: The paper presents a novel deep learning approach, which extracts latent information from trained Deep Neural Networks (DNNs) and derives concise representations that are analyzed in an effective, transparent way for prediction in medical imaging. A novel methodology is presented, in which deep neural architectures that have been trained to provide highly accurate predictions over existing datasets are adapted, in a consistent way, to make predictions over different contexts and datasets. Unified prediction is then achieved over the original and the new datasets. Successful application is illustrated through a large experimental study for prediction of Parkinson’s disease from MRI and DaTScans, as well as for prediction of COVID-19 from CT scans and X-rays.

Reducing Waste to Landfill in the UK: Identifying Impediments and Critical Solutions

Abstract: Purpose – The UK construction industry produces up to one third of all waste to landfill. This study aims to identify specific project practices impeding the reduction of waste in construction projects as well as uncovering potential waste solutions throughout the project delivery process. The rationale being that for such a drastic reduction in waste to landfill, holistic and extensive measures would be required.Design/methodology/approach – A two‐way methodological approach was used. This comprised qualitative unstructured interviews and a quantitative questionnaire survey of three major stakeholders in the UK construction industry: clients, architects and contractors.Findings – Design factors remain the major cause of impediments to waste reduction to landfill. Critical impediments include clients making waste prevention a top priority in projects, overly complex designs, waste taking a low priority compared to project time and costs, lack of concerns by designers for buildability, among others. Critic...

Efficient Online Subspace Learning With an Indefinite Kernel for Visual Tracking and Recognition

Abstract: We propose an exact framework for online learning with a family of indefinite (not positive) kernels. As we study the case of nonpositive kernels, we first show how to extend kernel principal component analysis (KPCA) from a reproducing kernel Hilbert space to Krein space. We then formulate an incremental KPCA in Krein space that does not require the calculation of preimages and therefore is both efficient and exact. Our approach has been motivated by the application of visual tracking for which we wish to employ a robust gradient-based kernel. We use the proposed nonlinear appearance model learned online via KPCA in Krein space for visual tracking in many popular and difficult tracking scenarios. We also show applications of our kernel framework for the problem of face recognition.