Results 211 to 220 of about 188,394 (267)

Improving Lidocaine Topicalisation Practices in Paediatric Airway Management: A Quality Improvement Project. [PDF]

Cureus
Whiteley C, Lodwick G.
europepmc   +1 more source

Genomics-informed approach identifies which cell types regulate the metabolome. [PDF]

Bioinformatics
Krupkin H, Padhi EM, Nachun D, Kain J, Long JZ, Montgomery SB.   +5 more
europepmc   +1 more source

Genetic Evidence Links Gestational Diabetes Mellitus to Increased ER-Negative Breast Cancer Risk Through a Mendelian Randomization Analysis. [PDF]

Int J Endocrinol
Peng W, Huang Z, Zhang M.
europepmc   +1 more source

Outliers (typically) cannot cause type I errors in one-sample/paired t-tests. [PDF]

PLoS One
Wisler A.
europepmc   +1 more source

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Adaptive outlierness for subspace outlier ranking

Proceedings of the 19th ACM international conference on Information and knowledge management, 2010
Outlier mining is an important data analysis task to distinguish exceptional outliers from regular objects. However, in recent applications traditional outlier mining approaches miss outliers as they are hidden in subspace projections. In this work, we propose a novel outlier ranking based on the degree of deviation in subspaces.
Emmanuel Müller, Matthias Schiffer, Thomas Seidl 0001   +2 more
openaire   +1 more source

On Evaluation of Outlier Rankings and Outlier Scores

Proceedings of the 2012 SIAM International Conference on Data Mining, 2012
Outlier detection research is currently focusing on the development of new methods and on improving the computation time for these methods. Evaluation however is rather heuristic, often considering just precision in the top k results or using the area under the ROC curve.
Erich Schubert, Remigius Wojdanowski, Arthur Zimek, Hans-Peter Kriegel   +3 more
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Enhancing Outlier Detection by an Outlier Indicator

2018
Outlier detection is an important task in data mining and has high practical value in numerous applications such as astronomical observation, text detection, fraud detection and so on. At present, a large number of popular outlier detection algorithms are available, including distribution-based, distance-based, density-based, and clustering-based ...
Xiaqiong Li, Xiaochun Wang, Xia Li Wang
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The Outlier

Hastings Center Report, 2013
AbstractAmy's excellent home care was the only reason she was doing as well as she was. There was no one better at taking care of Amy than her husband. When she had a respiratory infection, Steve managed the necessary increased suctioning, nebulizer treatments, and ventilator, in addition to all the other intimate personal assistance she needed on a ...
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When is an outlier not an outlier?

NIR news, 2019
The tendency of the users of NIRS is to think of the composition particularly in terms of the reference data, for the prediction of which the technique is to be used. The concept and principle of NIRS analysis differ from classical chemical analysis in that NIRS is based exclusively on the spectra.
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Separability with Outliers

2005
We develop exact and approximate algorithms for computing optimal separators and measuring the extent to which two point sets in d-dimensional space are separated, with respect to different classes of separators and various extent measures. This class of geometric problems generalizes two widely studied problem families, namely separability and the ...
Sariel Har-Peled, Vladlen Koltun
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