Institution
Indiana University
Education•Bloomington, Indiana, United States•
About: Indiana University is a education organization based out in Bloomington, Indiana, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 64480 authors who have published 150058 publications receiving 6392902 citations. The organization is also known as: Indiana University system & indiana.edu.
Topics: Population, Poison control, Context (language use), Health care, Cancer
Papers published on a yearly basis
Papers
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TL;DR: Synthesis of six case studies from around the world shows that couplings between human and natural systems vary across space, time, and organizational units and have legacy effects on present conditions and future possibilities.
Abstract: Integrated studies of coupled human and natural systems reveal new and complex patterns and processes not evident when studied by social or natural scientists separately. Synthesis of six case studies from around the world shows that couplings between human and natural systems vary across space, time, and organizational units. They also exhibit nonlinear dynamics with thresholds, reciprocal feedback loops, time lags, resilience, heterogeneity, and surprises. Furthermore, past couplings have legacy effects on present conditions and future possibilities.
2,890 citations
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TL;DR: In this paper, it was shown that modularity optimization may fail to identify modules smaller than a scale which depends on the total size of the network and the degree of interconnectedness of the modules, even in cases where modules are unambiguously defined.
Abstract: Detecting community structure is fundamental for uncovering the links between structure and function in complex networks and for practical applications in many disciplines such as biology and sociology. A popular method now widely used relies on the optimization of a quantity called modularity, which is a quality index for a partition of a network into communities. We find that modularity optimization may fail to identify modules smaller than a scale which depends on the total size of the network and on the degree of interconnectedness of the modules, even in cases where modules are unambiguously defined. This finding is confirmed through several examples, both in artificial and in real social, biological, and technological networks, where we show that modularity optimization indeed does not resolve a large number of modules. A check of the modules obtained through modularity optimization is thus necessary, and we provide here key elements for the assessment of the reliability of this community detection method.
2,829 citations
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TL;DR: In this article, the authors explore the conceptual origins of the community, and the ways the term has been deployed in writings on resource use, and analyze those aspects of community most important to advocates for community's role in resource management.
2,826 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
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TL;DR: This paper is a comprehensive exploration of all the major change detection approaches implemented as found in the literature and summarizes and reviews these techniques.
Abstract: Timely and accurate change detection of Earth's surface features is extremely important for understanding relationships and interactions between human and natural phenomena in order to promote better decision making. Remote sensing data are primary sources extensively used for change detection in recent decades. Many change detection techniques have been developed. This paper summarizes and reviews these techniques. Previous literature has shown that image differencing, principal component analysis and post-classification comparison are the most common methods used for change detection. In recent years, spectral mixture analysis, artificial neural networks and integration of geographical information system and remote sensing data have become important techniques for change detection applications. Different change detection algorithms have their own merits and no single approach is optimal and applicable to all cases. In practice, different algorithms are often compared to find the best change detection results for a specific application. Research of change detection techniques is still an active topic and new techniques are needed to effectively use the increasingly diverse and complex remotely sensed data available or projected to be soon available from satellite and airborne sensors. This paper is a comprehensive exploration of all the major change detection approaches implemented as found in the literature.
2,785 citations
Authors
Showing all 64884 results
Name | H-index | Papers | Citations |
---|---|---|---|
Frank B. Hu | 250 | 1675 | 253464 |
Stuart H. Orkin | 186 | 715 | 112182 |
Bruce M. Spiegelman | 179 | 434 | 158009 |
David R. Williams | 178 | 2034 | 138789 |
D. M. Strom | 176 | 3167 | 194314 |
Markus Antonietti | 176 | 1068 | 127235 |
Lei Jiang | 170 | 2244 | 135205 |
Brenda W.J.H. Penninx | 170 | 1139 | 119082 |
Nahum Sonenberg | 167 | 647 | 104053 |
Carl W. Cotman | 165 | 809 | 105323 |
Yang Yang | 164 | 2704 | 144071 |
Jaakko Kaprio | 163 | 1532 | 126320 |
Ralph A. DeFronzo | 160 | 759 | 132993 |
Gavin Davies | 159 | 2036 | 149835 |
Tyler Jacks | 158 | 463 | 115172 |