Institution
McGill University
Education•Montreal, Quebec, Canada•
About: McGill University is a education organization based out in Montreal, Quebec, Canada. It is known for research contribution in the topics: Population & Context (language use). The organization has 72688 authors who have published 162565 publications receiving 6966523 citations. The organization is also known as: Royal institution of advanced learning & University of McGill College.
Topics: Population, Context (language use), Poison control, Health care, Cancer
Papers published on a yearly basis
Papers
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Jean-Charles Lambert1, Jean-Charles Lambert2, Jean-Charles Lambert3, Carla A. Ibrahim-Verbaas4 +212 more•Institutions (75)
TL;DR: In addition to the APOE locus (encoding apolipoprotein E), 19 loci reached genome-wide significance (P < 5 × 10−8) in the combined stage 1 and stage 2 analysis, of which 11 are newly associated with Alzheimer's disease.
Abstract: Eleven susceptibility loci for late-onset Alzheimer's disease (LOAD) were identified by previous studies; however, a large portion of the genetic risk for this disease remains unexplained. We conducted a large, two-stage meta-analysis of genome-wide association studies (GWAS) in individuals of European ancestry. In stage 1, we used genotyped and imputed data (7,055,881 SNPs) to perform meta-analysis on 4 previously published GWAS data sets consisting of 17,008 Alzheimer's disease cases and 37,154 controls. In stage 2, 11,632 SNPs were genotyped and tested for association in an independent set of 8,572 Alzheimer's disease cases and 11,312 controls. In addition to the APOE locus (encoding apolipoprotein E), 19 loci reached genome-wide significance (P < 5 × 10−8) in the combined stage 1 and stage 2 analysis, of which 11 are newly associated with Alzheimer's disease.
3,726 citations
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TL;DR: It is asserted that community ecology should return to an emphasis on four themes that are tied together by a two-step process: how the fundamental niche is governed by functional traits within the context of abiotic environmental gradients; and how the interaction between traits and fundamental niches maps onto the realized niche in the context a biotic interaction milieu.
Abstract: There is considerable debate about whether community ecology will ever produce general principles. We suggest here that this can be achieved but that community ecology has lost its way by focusing on pairwise species interactions independent of the environment. We assert that community ecology should return to an emphasis on four themes that are tied together by a two-step process: how the fundamental niche is governed by functional traits within the context of abiotic environmental gradients; and how the interaction between traits and fundamental niches maps onto the realized niche in the context of a biotic interaction milieu. We suggest this approach can create a more quantitative and predictive science that can more readily address issues of global change.
3,715 citations
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Technische Universität München1, ETH Zurich2, University of Bern3, Harvard University4, National Institutes of Health5, University of Debrecen6, University Hospital Heidelberg7, McGill University8, University of Pennsylvania9, French Institute for Research in Computer Science and Automation10, University at Buffalo11, Microsoft12, University of Cambridge13, Stanford University14, University of Virginia15, Imperial College London16, Massachusetts Institute of Technology17, Columbia University18, Sabancı University19, Old Dominion University20, RMIT University21, Purdue University22, General Electric23
TL;DR: The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) as mentioned in this paper was organized in conjunction with the MICCAI 2012 and 2013 conferences, and twenty state-of-the-art tumor segmentation algorithms were applied to a set of 65 multi-contrast MR scans of low and high grade glioma patients.
Abstract: In this paper we report the set-up and results of the Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) organized in conjunction with the MICCAI 2012 and 2013 conferences Twenty state-of-the-art tumor segmentation algorithms were applied to a set of 65 multi-contrast MR scans of low- and high-grade glioma patients—manually annotated by up to four raters—and to 65 comparable scans generated using tumor image simulation software Quantitative evaluations revealed considerable disagreement between the human raters in segmenting various tumor sub-regions (Dice scores in the range 74%–85%), illustrating the difficulty of this task We found that different algorithms worked best for different sub-regions (reaching performance comparable to human inter-rater variability), but that no single algorithm ranked in the top for all sub-regions simultaneously Fusing several good algorithms using a hierarchical majority vote yielded segmentations that consistently ranked above all individual algorithms, indicating remaining opportunities for further methodological improvements The BRATS image data and manual annotations continue to be publicly available through an online evaluation system as an ongoing benchmarking resource
3,699 citations
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TL;DR: If the organism is severely damaged by acute non-specific nocuous agents such as exposure to cold, surgical injury, production of spinal shock, excessive muscular exercise, or intoxications with sublethal doses of diverse drugs, a typical syndrome appears, the symptoms of which are independent of the nature of the damaging agent or the pharmacological type of the drug employed.
Abstract: EXPERIMENTS on rats show that if the organism is severely damaged by acute non-specific nocuous agents such as exposure to cold, surgical injury, production of spinal shock (transcision of the cord), excessive muscular exercise, or intoxications with sublethal doses of diverse drugs (adrenaline, atropine, morphine, formaldehyde, etc.), a typical syndrome appears, the symptoms of which are independent of the nature of the damaging agent or the pharmacological type of the drug employed, and represent rather a response to damage as such.
3,667 citations
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TL;DR: A parallel distributed processing model of visual word recognition and pronunciation is described, which consists of sets of orthographic and phonological units and an interlevel of hidden units and which early in the learning phase corresponds to that of children acquiring word recognition skills.
Abstract: A parallel distributed processing model of visual word recognition and pronunciation is described. The model consists of sets of orthographic and phonological units and an interlevel of hidden units. Weights on connections between units were modified during a training phase using the back-propagation learning algorithm. The model simulates many aspects of human performance, including (a) differences between words in terms of processing difficulty, (b) pronunciation of novel items, (c) differences between readers in terms of word recognition skill, (d) transitions from beginning to skilled reading, and (e) differences in performance on lexical decision and naming tasks. The model's behavior early in the learning phase corresponds to that of children acquiring word recognition skills. Training with a smaller number of hidden units produces output characteristic of many dyslexic readers. Naming is simulated without pronunciation rules, and lexical decisions are simulated without accessing word-level representations. The performance of the model is largely determined by three factors: the nature of the input, a significant fragment of written English; the learning rule, which encodes the implicit structure of the orthography in the weights on connections; and the architecture of the system, which influences the scope of what can be learned.
3,642 citations
Authors
Showing all 73373 results
Name | H-index | Papers | Citations |
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Karl J. Friston | 217 | 1267 | 217169 |
Yi Chen | 217 | 4342 | 293080 |
Yoshua Bengio | 202 | 1033 | 420313 |
Irving L. Weissman | 201 | 1141 | 172504 |
Mark I. McCarthy | 200 | 1028 | 187898 |
Lewis C. Cantley | 196 | 748 | 169037 |
Martin White | 196 | 2038 | 232387 |
Michael Marmot | 193 | 1147 | 170338 |
Michael A. Strauss | 185 | 1688 | 208506 |
Alan C. Evans | 183 | 866 | 134642 |
Douglas R. Green | 182 | 661 | 145944 |
David A. Weitz | 178 | 1038 | 114182 |
David L. Kaplan | 177 | 1944 | 146082 |
Hyun-Chul Kim | 176 | 4076 | 183227 |
Feng Zhang | 172 | 1278 | 181865 |