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Outlier detection
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The study objective was to evaluate the accuracy, validity, and clinical usefulness of medication error alerts generated by an alerting system using outlier detection screening. The screening system was able to generate alerts that might otherwise be missed with existing CDS systems and did so with a reasonably high degree of alert usefulness when subjected to review of patients’ clinical contexts and details.
7p
visteverogers
24-06-2023
5
3
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Lecture Business statistics - Chapter 3: Descriptive statistics - Numerical measures. The main topics covered in this chapter include: measures of location; measures of variability; measures of distributional shape, relative location and detecting outliers; exploratory data analysis; measures of association between two variables;... Please refer to the lecture for details!
27p
chutieubang
06-12-2022
13
2
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Lecture Data mining: Lesson 21. The main topics covered in this chapter include: outlier discovery/anomaly detection; credit card fraud detection; telecommunication fraud detection; network intrusion detection; fault detection;... Please refer to the content of document.
20p
tieuvulinhhoa
22-09-2022
11
3
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The problem of finding anomalies and outliers in datasets is one of the most important challenges of modern data analysis. Among the commonly dedicated tools to solve this task one can find Isolation Forest (IF) that is an efficient, conceptually simple, and fast method.
17p
guernsey
28-12-2021
12
0
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In this paper, we have set up an approach to detect botnet of IoT devices using three one-class classi¯er ML algorithms. The algorithms are: one-class support vector machine (OCSVM), elliptic envelope (EE), and local outlier factor (LOF).
20p
redemption
20-12-2021
20
1
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Genome scans based on outlier analyses have revolutionized detection of genes involved in adaptive processes, but reports of some forms of selection, such as balancing selection, are still limited. It is unclear whether high throughput genotyping approaches for identification of single nucleotide polymorphisms have sufficient power to detect modes of selection expected to result in reduced genetic differentiation among populations.
21p
vibeauty
23-10-2021
6
1
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Sequence data used in reconstructing phylogenetic trees may include various sources of error. Typically errors are detected at the sequence level, but when missed, the erroneous sequences often appear as unexpectedly long branches in the inferred phylogeny.
18p
vibeauty
23-10-2021
5
1
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Heterogeneously and differentially expressed genes (hDEG) are a common phenomenon due to bio-logical diversity. A hDEG is often observed in gene expression experiments (with two experimental conditions) where it is highly expressed in a few experimental samples, or in drug trial experiments for cancer studies with drug resistance heterogeneity among the disease group.
10p
viwyoming2711
16-12-2020
9
1
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Genome-wide association studies can provide novel insights into diseases of interest, as well as to the responsiveness of an individual to specific treatments. In such studies, it is very important to correct for population stratification, which refers to allele frequency differences between cases and controls due to systematic ancestry differences.
12p
viwyoming2711
16-12-2020
11
0
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This paper describes a simple method for automatically detecting outliers and accompanying software called OD-seq. It is based on finding sequences whose average distance to the rest of the sequences in a dataset, is anomalous.
11p
vikentucky2711
24-11-2020
6
1
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The inference of complex networks from data is a challenging problem in biological sciences, as well as in a wide range of disciplines such as chemistry, technology, economics, or sociology. The quantity and quality of the data greatly affect the results.
12p
vikentucky2711
24-11-2020
9
1
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Learning accurate models from ‘omics data is bringing many challenges due to their inherent high-dimensionality, e.g. the number of gene expression variables, and comparatively lower sample sizes, which leads to ill-posed inverse problems.
15p
viconnecticut2711
28-10-2020
17
0
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An important issue in microarray data is to select, from thousands of genes, a small number of informative differentially expressed (DE) genes which may be key elements for a disease. If each gene is analyzed individually, there is a big number of hypotheses to test and a multiple comparison correction method must be used.
20p
viconnecticut2711
28-10-2020
28
1
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High throughput RNA sequencing is a powerful approach to study gene expression. Due to the complex multiple-steps protocols in data acquisition, extreme deviation of a sample from samples of the same treatment group may occur due to technical variation or true biological differences.
20p
vicolorado2711
22-10-2020
8
0
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Previous studies have reported that labeling errors are not uncommon in omics data. Potential outliers may severely undermine the correct classification of patients and the identification of reliable biomarkers for a particular disease.
23p
vicolorado2711
22-10-2020
7
0
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In methylation analyses like epigenome-wide association studies, a high amount of biomarkers is tested for an association between the measured continuous outcome and different covariates. In the case of a continuous covariate like smoking pack years (SPY), a measure of lifetime exposure to tobacco toxins, a spike at zero can occur.
14p
vicolorado2711
22-10-2020
9
0
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The Nearest Neighbour Search is one of these techniques. It uses the Euclidean or Mahalanobis distance for detecting outliers in a given sensor networks. In this paper, we proposed a distributed adaptive approach for the detection of outliers. The proposed approach is based on Euclidean or Mahalanobis distance, depending on the size of the data collected. Extensive experiments have been conducted and the results confirmed the effectiveness of the proposal.
10p
blossom162
31-03-2019
36
1
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This paper presents the results of an experimental study of some common intrusion detection techniques. In particular we compared the three main approaches to intrusion detection: FCC, Y-Means, and UAD. The aim of this study is to compare and find feasible clustering algorithms to achieve good performance with high efficiency while dealing with the intrusions.
6p
byphasse043256
24-03-2019
34
0
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Lectures "Applied statistics for business - Chapter 3: Numerical measures" provides students with the knowledge: Measures of location, measures of variability, measures of distribution shape, relative location, and detection of outliers. Invite you to refer to the disclosures.
45p
doinhugiobay_13
26-01-2016
49
3
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We have developed an automated Japanese essay scoring system called Jess. The system needs expert writings rather than expert raters to build the evaluation model. By detecting statistical outliers of predetermined aimed essay features compared with many professional writings for each prompt, our system can evaluate essays.
8p
hongvang_1
16-04-2013
46
1
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