Institution
University of Rochester
Education•Rochester, New York, United States•
About: University of Rochester is a education organization based out in Rochester, New York, United States. It is known for research contribution in the topics: Population & Laser. The organization has 63915 authors who have published 112762 publications receiving 5484122 citations. The organization is also known as: Rochester University.
Topics: Population, Laser, Poison control, Health care, Context (language use)
Papers published on a yearly basis
Papers
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TL;DR: This paper identifies several serious problems with the widespread use of ANOVAs for the analysis of categorical outcome variables, and introduces ordinary logit models (i.e. logistic regression), which are well-suited to analyze categorical data and offer many advantages over ANOVA.
2,895 citations
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18 Jun 2018TL;DR: This paper proposes residual dense block (RDB) to extract abundant local features via dense connected convolutional layers and uses global feature fusion in RDB to jointly and adaptively learn global hierarchical features in a holistic way.
Abstract: A very deep convolutional neural network (CNN) has recently achieved great success for image super-resolution (SR) and offered hierarchical features as well. However, most deep CNN based SR models do not make full use of the hierarchical features from the original low-resolution (LR) images, thereby achieving relatively-low performance. In this paper, we propose a novel residual dense network (RDN) to address this problem in image SR. We fully exploit the hierarchical features from all the convolutional layers. Specifically, we propose residual dense block (RDB) to extract abundant local features via dense connected convolutional layers. RDB further allows direct connections from the state of preceding RDB to all the layers of current RDB, leading to a contiguous memory (CM) mechanism. Local feature fusion in RDB is then used to adaptively learn more effective features from preceding and current local features and stabilizes the training of wider network. After fully obtaining dense local features, we use global feature fusion to jointly and adaptively learn global hierarchical features in a holistic way. Experiments on benchmark datasets with different degradation models show that our RDN achieves favorable performance against state-of-the-art methods.
2,860 citations
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2,844 citations
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TL;DR: It is argued that the regulation of intentional behavior varies along a continuum from autonomous (i.e., self-determined) to controlled, with a particular emphasis on its implications for the study of social psychology and personality.
Abstract: In this article we suggest that events and contexts relevant to the initiation and regulation of intentional behavior can function either to support autonomy (i.e., to promote choice) or to control behavior (i.e., to pressure one toward specific outcomes). Research herein reviewed indicates that this distinction is relevant to specific external events and to general interpersonal contexts as well as to specific internal events and to general personality orientations. That is, the distinction is relevant whether one's analysis focuses on social psychological variables or on personality variables. The research review details those contextual and person factors that tend to promote autonomy and those that tend to control. Furthermore, it shows that autonomy support has generally been associated with more intrinsic motivation, greater interest, less pressure and tension, more creativity, more cognitive flexibility, better conceptual learning, a more positive emotional tone, higher self-esteem, more trust, greater persistence of behavior change, and better physical and psychological health than has control. Also, these results have converged across different assessment procedures, different research methods, and different subject populations. On the basis or these results, we present an organismic perspective in which we argue that the regulation of intentional behavior varies along a continuum from autonomous (i.e.. self-determined) to controlled. The relation of this organismic perspective to historical developments in empirical psychology is discussed, with a particular emphasis on its implications for the study of social psychology and personality. For several decades American psychology was dominated by associationist theories. Assuming that behavior is controlled by peripheral mechanisms, these theories held that the initiation of behavior is a function of stimulus inputs such as external contingencies of reinforcement (Skinner, 1953) or internal drive stimulations (Hull, 1943) and that the regulation of behavior is a function of associative bonds between inputs and behaviors that develop through reinforcement processes. With that general perspective, the central processing of information was not part of the explanatory system, so concepts such as intention were considered irrelevant to the determination of be
2,824 citations
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Johns Hopkins University1, University of Utah2, University of Rochester3, The Royal Marsden NHS Foundation Trust4, National Institutes of Health5, Stanford University6, Washington University in St. Louis7, Ontario Institute for Cancer Research8, University of Sydney9, St. Jude Medical Center10, University of Toronto11, Mayo Clinic12, American Society of Clinical Oncology13, University of Southern California14, North Carolina State University15, Indiana University16, University of Milan17, University of Michigan18
TL;DR: The Update Committee recommends that HER2 status (HER2 negative or positive) be determined in all patients with invasive breast cancer on the basis of one or more HER2 test results (negative, equivocal, or positive).
Abstract: Purpose.—To update the American Society of Clinical Oncology (ASCO)/College of American Pathologists (CAP) guideline recommendations for human epidermal growth factor receptor 2 (HER2) testing in b...
2,817 citations
Authors
Showing all 64186 results
Name | H-index | Papers | Citations |
---|---|---|---|
Eugene Braunwald | 230 | 1711 | 264576 |
Cyrus Cooper | 204 | 1869 | 206782 |
Eric J. Topol | 193 | 1373 | 151025 |
Dennis W. Dickson | 191 | 1243 | 148488 |
Scott M. Grundy | 187 | 841 | 231821 |
John C. Morris | 183 | 1441 | 168413 |
Ronald C. Petersen | 178 | 1091 | 153067 |
David R. Williams | 178 | 2034 | 138789 |
John Hardy | 177 | 1178 | 171694 |
Russel J. Reiter | 169 | 1646 | 121010 |
Michael Snyder | 169 | 840 | 130225 |
Jiawei Han | 168 | 1233 | 143427 |
Gang Chen | 167 | 3372 | 149819 |
Marc A. Pfeffer | 166 | 765 | 133043 |
Salvador Moncada | 164 | 495 | 138030 |