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Institution

University of Groningen

EducationGroningen, Groningen, Netherlands
About: University of Groningen is a education organization based out in Groningen, Groningen, Netherlands. It is known for research contribution in the topics: Population & Poison control. The organization has 36346 authors who have published 69116 publications receiving 2940370 citations. The organization is also known as: Rijksuniversiteit Groningen & RUG.


Papers
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Journal ArticleDOI
Douglas M. Ruderfer1, Stephan Ripke2, Stephan Ripke3, Stephan Ripke4  +628 moreInstitutions (156)
14 Jun 2018-Cell
TL;DR: For the first time, specific loci that distinguish between BD and SCZ are discovered and polygenic components underlying multiple symptom dimensions are identified that point to the utility of genetics to inform symptomology and potential treatment.

569 citations

Journal ArticleDOI
05 Jul 2021-PeerJ
TL;DR: In this paper, the authors compare the performance of R-squared and SMAPE with respect to the distribution of ground truth elements, and show that the coefficient of determination is more informative and truthful than SMAPE, and does not have the interpretability limitations of MSE, RMSE, MAE and MAPE.
Abstract: Regression analysis makes up a large part of supervised machine learning, and consists of the prediction of a continuous independent target from a set of other predictor variables. The difference between binary classification and regression is in the target range: in binary classification, the target can have only two values (usually encoded as 0 and 1), while in regression the target can have multiple values. Even if regression analysis has been employed in a huge number of machine learning studies, no consensus has been reached on a single, unified, standard metric to assess the results of the regression itself. Many studies employ the mean square error (MSE) and its rooted variant (RMSE), or the mean absolute error (MAE) and its percentage variant (MAPE). Although useful, these rates share a common drawback: since their values can range between zero and +infinity, a single value of them does not say much about the performance of the regression with respect to the distribution of the ground truth elements. In this study, we focus on two rates that actually generate a high score only if the majority of the elements of a ground truth group has been correctly predicted: the coefficient of determination (also known as R-squared or R 2) and the symmetric mean absolute percentage error (SMAPE). After showing their mathematical properties, we report a comparison between R 2 and SMAPE in several use cases and in two real medical scenarios. Our results demonstrate that the coefficient of determination (R-squared) is more informative and truthful than SMAPE, and does not have the interpretability limitations of MSE, RMSE, MAE and MAPE. We therefore suggest the usage of R-squared as standard metric to evaluate regression analyses in any scientific domain.

568 citations

Journal ArticleDOI
24 Jan 1997-Science
TL;DR: Intravenous administration of the antibody-tTF complex to mice with large neuroblastomas resulted in complete tumor regressions in 38 percent of the mice, indicating an effective and selective thrombogen when targeted to tumor endothelial cells.
Abstract: Selective occlusion of tumor vasculature was tested as a therapy for solid tumors in a mouse model. The formation of blood clots (thrombosis) within the tumor vessels was initiated by targeting the cell surface domain of human tissue factor, by means of a bispecific antibody, to an experimentally induced marker on tumor vascular endothelial cells. This truncated form of tissue factor (tTF) had limited ability to initiate thrombosis when free in the circulation, but became an effective and selective thrombogen when targeted to tumor endothelial cells. Intravenous administration of the antibody-tTF complex to mice with large neuroblastomas resulted in complete tumor regressions in 38 percent of the mice.

567 citations

Journal ArticleDOI
TL;DR: It is shown that despite the weakness of gravity, the phase evolution induced by the gravitational interaction of two micron size test masses in adjacent matter-wave interferometers can detectably entangle them even when they are placed far apart enough to keep Casimir-Polder forces at bay.
Abstract: Understanding gravity in the framework of quantum mechanics is one of the great challenges in modern physics. However, the lack of empirical evidence has lead to a debate on whether gravity is a quantum entity. Despite varied proposed probes for quantum gravity, it is fair to say that there are no feasible ideas yet to test its quantum coherent behavior directly in a laboratory experiment. Here, we introduce an idea for such a test based on the principle that two objects cannot be entangled without a quantum mediator. We show that despite the weakness of gravity, the phase evolution induced by the gravitational interaction of two micron size test masses in adjacent matter-wave interferometers can detectably entangle them even when they are placed far apart enough to keep Casimir-Polder forces at bay. We provide a prescription for witnessing this entanglement, which certifies gravity as a quantum coherent mediator, through simple spin correlation measurements.

567 citations

Journal ArticleDOI
TL;DR: Based on the anatomical connections of these areas, and the Hebbian learning rule, a simple but powerful account of how the monkey brain can learn to understand the actions of others by associating them with self-produced actions, at the also discriminating its own actions from those of others is proposed.

565 citations


Authors

Showing all 36692 results

NameH-indexPapersCitations
Ronald C. Kessler2741332328983
Nicholas J. Wareham2121657204896
André G. Uitterlinden1991229156747
Lei Jiang1702244135205
Brenda W.J.H. Penninx1701139119082
Richard H. Friend1691182140032
Panos Deloukas162410154018
Jerome I. Rotter1561071116296
Christopher M. Dobson1501008105475
Dirk Inzé14964774468
Scott T. Weiss147102574742
Dieter Lutz13967167414
Wilmar B. Schaufeli13751395718
Cisca Wijmenga13666886572
Arnold B. Bakker135506103778
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023166
2022543
20214,487
20203,990
20193,283
20182,836