Institution
University of Queensland
Education•Brisbane, Queensland, Australia•
About: University of Queensland is a education organization based out in Brisbane, Queensland, Australia. It is known for research contribution in the topics: Population & Poison control. The organization has 51138 authors who have published 155721 publications receiving 5717659 citations. The organization is also known as: UQ & The University of Queensland.
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TL;DR: Although there is considerable uncertainty about the spatial and temporal details, climate change is clearly and fundamentally altering ocean ecosystems and will continue to create enormous challenges and costs for societies worldwide, particularly those in developing countries.
Abstract: Marine ecosystems are centrally important to the biology of the planet, yet a comprehensive understanding of how anthropogenic climate change is affecting them has been poorly developed. Recent studies indicate that rapidly rising greenhouse gas concentrations are driving ocean systems toward conditions not seen for millions of years, with an associated risk of fundamental and irreversible ecological transformation. The impacts of anthropogenic climate change so far include decreased ocean productivity, altered food web dynamics, reduced abundance of habitat-forming species, shifting species distributions, and a greater incidence of disease. Although there is considerable uncertainty about the spatial and temporal details, climate change is clearly and fundamentally altering ocean ecosystems. Further change will continue to create enormous challenges and costs for societies worldwide, particularly those in developing countries.
2,408 citations
University of Washington1, Institute for Health Metrics and Evaluation2, Iran University of Medical Sciences3, King's College London4, Arabian Gulf University5, University of North Texas6, Auckland University of Technology7, Alaska Native Tribal Health Consortium8, Columbia University9, Wuhan University10, Imperial College London11, University of Alabama at Birmingham12, University at Albany, SUNY13, City University of New York14, University of California, San Francisco15, Griffith University16, Environment Agency17, New York University18, Southern University College19, Emory University20, University of Ottawa21, Kosin University22, University of Toronto23, University of British Columbia24, United Arab Emirates University25, Albert Einstein College of Medicine26, University of São Paulo27, Nova Southeastern University28, University of Sydney29, Heidelberg University30, Cancer Treatment Centers of America31, Case Western Reserve University32, University of Oxford33, George Mason University34, James Cook University35, University of Trieste36, University of Calgary37, Wageningen University and Research Centre38, University of the Witwatersrand39, University of Gothenburg40, Harvard University41, Jackson State University42, University of Arizona43, University of Hong Kong44, Tehran University of Medical Sciences45, University of Western Australia46, Aintree University Hospitals NHS Foundation Trust47, University of Colorado Denver48, Veterans Health Administration49, Royal Children's Hospital50, University of Melbourne51, Australian National University52, University of Marburg53, Charité54, Health Canada55, College of Health Sciences, Bahrain56, Karolinska Institutet57, Northumbria University58, University of Edinburgh59, National Research University – Higher School of Economics60, Queen Mary University of London61, Addis Ababa University62, Northwestern University63, Northeastern University64, Mario Negri Institute for Pharmacological Research65, Arak University of Medical Sciences66, University of Nottingham67, University of Tokyo68, Public Health Foundation of India69, University of Groningen70, University of the Philippines Manila71, University of Bologna72, Kyung Hee University73, Brighton and Sussex Medical School74, Stavanger University Hospital75, University of Bergen76, University of Queensland77, National Centre for Disease Control78, University of Sheffield79, Universidad Autónoma Metropolitana80, University College London81, Genentech82, Universiti Tunku Abdul Rahman83, Norwegian Institute of Public Health84
TL;DR: To estimate mortality, incidence, years lived with disability, years of life lost, and disability-adjusted life-years for 28 cancers in 188 countries by sex from 1990 to 2013, the general methodology of the Global Burden of Disease 2013 study was used.
Abstract: Importance Cancer is among the leading causes of death worldwide. Current estimates of cancer burden in individual countries and regions are necessary to inform local cancer control strategies. Objective To estimate mortality, incidence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs) for 28 cancers in 188 countries by sex from 1990 to 2013. Evidence Review The general methodology of the Global Burden of Disease (GBD) 2013 study was used. Cancer registries were the source for cancer incidence data as well as mortality incidence (MI) ratios. Sources for cause of death data include vital registration system data, verbal autopsy studies, and other sources. The MI ratios were used to transform incidence data to mortality estimates and cause of death estimates to incidence estimates. Cancer prevalence was estimated using MI ratios as surrogates for survival data; YLDs were calculated by multiplying prevalence estimates with disability weights, which were derived from population-based surveys; YLLs were computed by multiplying the number of estimated cancer deaths at each age with a reference life expectancy; and DALYs were calculated as the sum of YLDs and YLLs. Findings In 2013 there were 14.9 million incident cancer cases, 8.2 million deaths, and 196.3 million DALYs. Prostate cancer was the leading cause for cancer incidence (1.4 million) for men and breast cancer for women (1.8 million). Tracheal, bronchus, and lung (TBL) cancer was the leading cause for cancer death in men and women, with 1.6 million deaths. For men, TBL cancer was the leading cause of DALYs (24.9 million). For women, breast cancer was the leading cause of DALYs (13.1 million). Age-standardized incidence rates (ASIRs) per 100 000 and age-standardized death rates (ASDRs) per 100 000 for both sexes in 2013 were higher in developing vs developed countries for stomach cancer (ASIR, 17 vs 14; ASDR, 15 vs 11), liver cancer (ASIR, 15 vs 7; ASDR, 16 vs 7), esophageal cancer (ASIR, 9 vs 4; ASDR, 9 vs 4), cervical cancer (ASIR, 8 vs 5; ASDR, 4 vs 2), lip and oral cavity cancer (ASIR, 7 vs 6; ASDR, 2 vs 2), and nasopharyngeal cancer (ASIR, 1.5 vs 0.4; ASDR, 1.2 vs 0.3). Between 1990 and 2013, ASIRs for all cancers combined (except nonmelanoma skin cancer and Kaposi sarcoma) increased by more than 10% in 113 countries and decreased by more than 10% in 12 of 188 countries. Conclusions and Relevance Cancer poses a major threat to public health worldwide, and incidence rates have increased in most countries since 1990. The trend is a particular threat to developing nations with health systems that are ill-equipped to deal with complex and expensive cancer treatments. The annual update on the Global Burden of Cancer will provide all stakeholders with timely estimates to guide policy efforts in cancer prevention, screening, treatment, and palliation.
2,375 citations
TL;DR: This tutorial presents the CE methodology, the basic algorithm and its modifications, and discusses applications in combinatorial optimization and machine learning.
Abstract: The cross-entropy (CE) method is a new generic approach to combinatorial and multi-extremal optimization and rare event simulation. The purpose of this tutorial is to give a gentle introduction to the CE method. We present the CE methodology, the basic algorithm and its modifications, and discuss applications in combinatorial optimization and machine learning.
2,367 citations
TL;DR: The past five years have seen many scientific and biological discoveries made through the experimental design of genome-wide association studies (GWASs), which were aimed at detecting variants at genomic loci that are associated with complex traits in the population and, in particular, at detecting associations between common single-nucleotide polymorphisms (SNPs) and common diseases such as heart disease, diabetes, auto-immune diseases, and psychiatric disorders.
Abstract: The past five years have seen many scientific and biological discoveries made through the experimental design of genome-wide association studies (GWASs). These studies were aimed at detecting variants at genomic loci that are associated with complex traits in the population and, in particular, at detecting associations between common single-nucleotide polymorphisms (SNPs) and common diseases such as heart disease, diabetes, auto-immune diseases, and psychiatric disorders. We start by giving a number of quotes from scientists and journalists about perceived problems with GWASs. We will then briefly give the history of GWASs and focus on the discoveries made through this experimental design, what those discoveries tell us and do not tell us about the genetics and biology of complex traits, and what immediate utility has come out of these studies. Rather than giving an exhaustive review of all reported findings for all diseases and other complex traits, we focus on the results for auto-immune diseases and metabolic diseases. We return to the perceived failure or disappointment about GWASs in the concluding section.
2,361 citations
University of Nebraska Medical Center1, University of Connecticut2, Harvard University3, Queen's University4, University of California, San Diego5, Stony Brook University6, University of Michigan7, National Institutes of Health8, Johns Hopkins University9, University of Barcelona10, University at Buffalo11, Summa Health System12, University of Texas Health Science Center at San Antonio13, University of Queensland14, Royal Brisbane and Women's Hospital15, University of Western Australia16, University of Colorado Denver17, McMaster University18
TL;DR: These guidelines are intended for use by healthcare professionals who care for patients at risk for hospital-acquired pneumonia (HAP) and ventilator-associated pneumonia (VAP), including specialists in infectious diseases, pulmonary diseases, critical care, and surgeons, anesthesiologists, hospitalists, and any clinicians and healthcare providers caring for hospitalized patients with nosocomial pneumonia.
Abstract: It is important to realize that guidelines cannot always account for individual variation among patients. They are not intended to supplant physician judgment with respect to particular patients or special clinical situations. IDSA considers adherence to these guidelines to be voluntary, with the ultimate determination regarding their application to be made by the physician in the light of each patient's individual circumstances.These guidelines are intended for use by healthcare professionals who care for patients at risk for hospital-acquired pneumonia (HAP) and ventilator-associated pneumonia (VAP), including specialists in infectious diseases, pulmonary diseases, critical care, and surgeons, anesthesiologists, hospitalists, and any clinicians and healthcare providers caring for hospitalized patients with nosocomial pneumonia. The panel's recommendations for the diagnosis and treatment of HAP and VAP are based upon evidence derived from topic-specific systematic literature reviews.
2,359 citations
Authors
Showing all 52145 results
| Name | H-index | Papers | Citations |
|---|---|---|---|
| Graham A. Colditz | 261 | 1542 | 256034 |
| George Davey Smith | 224 | 2540 | 248373 |
| David J. Hunter | 213 | 1836 | 207050 |
| Daniel Levy | 212 | 933 | 194778 |
| Christopher J L Murray | 209 | 754 | 310329 |
| Matthew Meyerson | 194 | 553 | 243726 |
| Luigi Ferrucci | 193 | 1601 | 181199 |
| Nicholas G. Martin | 192 | 1770 | 161952 |
| Paul M. Thompson | 183 | 2271 | 146736 |
| Jie Zhang | 178 | 4857 | 221720 |
| Alan D. Lopez | 172 | 863 | 259291 |
| Ian J. Deary | 166 | 1795 | 114161 |
| Steven N. Blair | 165 | 879 | 132929 |
| Carlos Bustamante | 161 | 770 | 106053 |
| David W. Johnson | 160 | 2714 | 140778 |