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Characterization of Non-hormone Expressing Endocrine Cells in Fetal and Infant Human Pancreas
Published 2019“…<h3>Context: </h3><p dir="ltr">Previously, we identified chromograninA positive hormone-negative (CPHN) cells in high frequency in human fetal and neonatal pancreas, likely representing nascent endocrine precursor cells. …”
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The global, regional, and national burden of inflammatory bowel disease in 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 20...
Published 2020“…To estimate the non-fatal burden, we used data presented in primary studies, hospital discharges, and claims data, and used DisMod-MR 2.1, a Bayesian meta-regression tool, to ensure consistency between measures. …”
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Global, regional, and national burden of respiratory tract cancers and associated risk factors from 1990 to 2019: a systematic analysis for the Global Burden of Disease Study 2019
Published 2021“…<h3>Background</h3><p dir="ltr">Prevention, control, and treatment of respiratory tract cancers are important steps towards achieving target 3.4 of the UN Sustainable Development Goals (SDGs)—a one-third reduction in premature mortality due to non-communicable diseases by 2030. …”
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The global, regional, and national burden of oesophageal cancer and its attributable risk factors in 195 countries and territories, 1990–2017: a systematic analysis for the Global...
Published 2020“…In 2017, age-standardised incidence was 2·7 times higher, mortality 2·9 times higher, and DALYs 3·0 times higher in males than in females. In 2017, a substantial proportion of oesophageal cancer DALYs were attributable to known risk factors: tobacco smoking (39·0% [35·5–42·2]), alcohol consumption (33·8% [27·3–39·9]), high BMI (19·5% [6·3–36·0]), a diet low in fruits (19·1% [4·2–34·6]), and use of chewing tobacco (7·5% [5·2–9·6]). …”
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The global, regional, and national burden of colorectal cancer and its attributable risk factors in 195 countries and territories, 1990–2017: a systematic analysis for the Global B...
Published 2019“…There was a non-linear association between the Socio-demographic Index and the Healthcare Access and Quality Index and age-standardised DALY rates. …”
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An ensemble-based machine learning model for predicting type 2 diabetes and its effect on bone health
Published 2024“…Therefore, early detection of diabetes would help to determine a proper diagnosis and treatment plan.</p><h3>Methods</h3><p dir="ltr">In this study, we employed machine learning (ML) based case-control study on a diabetic cohort size of 1000 participants form Qatar Biobank to predict diabetes using clinical and bone health indicators from Dual Energy X-ray Absorptiometry (DXA) machines. …”
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