Results 11 to 20 of about 11,013,156 (214)
Multivariate Behavioral Research, 2011 The propensity score is the probability of treatment assignment conditional on observed baseline characteristics. The propensity score allows one to design and analyze an observational (nonrandomized) study so that it mimics some of the particular ...
P. Austin
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Score-CAM: Score-Weighted Visual Explanations for Convolutional Neural Networks [PDF]
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2019 Recently, increasing attention has been drawn to the internal mechanisms of convolutional neural networks, and the reason why the network makes specific decisions.
Haofan Wang +7 more
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Journal of Patient-Reported Outcomes, 2022 Background As patient-reported outcome measures (PROMs) have become of significant importance in patient evaluation, adequately selecting the appropriate instrument is an integral part of pediatric orthopedic research and clinical practice.
J. P. Ruben Kalle +4 more
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Nature, 1977 Peter Pockley reports from Sydney on Australia's data collecting project for research ...
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Statistics in Medicine, 2009 The propensity score is a subject's probability of treatment, conditional on observed baseline covariates. Conditional on the true propensity score, treated and untreated subjects have similar distributions of observed baseline covariates.
P. Austin
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OER relevance attribution: educational dialogue with employers around curricular employability in HE
Journal of Interactive Media in Education, 2012 Graduate-recruiting employers can take part in an educational dialogue with HE practitioners around employability-related OER in the area of Arts and Humanities.
Antonio Martínez-Arboleda
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Some Practical Guidance for the Implementation of Propensity Score Matching
Social Science Research Network, 2008 Propensity Score Matching (PSM) has become a popular approach to estimate causal treatment effects. It is widely applied when evaluating labour market policies, but empirical examples can be found in very diverse fields of study.
Marco Caliendo, Sabine Kopeinig
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Context-Aware Process Performance Indicator Prediction
IEEE Access, 2020 It is well-known that context impacts running instances of a process. Thus, defining and using contextual information may help to improve the predictive monitoring of business processes, which is one of the main challenges in process mining.
Alfonso E. Marquez-Chamorro +5 more
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On scores, losing scores and total scores in hypertournaments
Electronic Journal of Graph Theory and Applications, 2015 Summary: A \(k\)-hypertournament is a complete \(k\)-hypergraph with each \(k\)-edge endowed with an orientation, that is, a linear arrangement of the vertices contained in the edge. In a \(k\)-hypertournament, the score \(s_i\) (losing score \(r_i)\) of a vertex \(v_i\) is the number of arcs containing \(v_i\) in which \(v_i\) is not the last element (
Shariefuddin Pirzada +3 more
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KofamKOALA: KEGG Ortholog assignment based on profile HMM and adaptive score threshold
bioRxiv, 2019 Summary KofamKOALA is a web server to assign KEGG Orthologs (KOs) to protein sequences by homology search against a database of profile hidden Markov models (KOfam) with pre-computed adaptive score thresholds.
T. Aramaki +6 more
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