Results 81 to 90 of about 23,619,888 (317)
FEBS Open Bio, EarlyView.KLK7, a tissue kallikrein‐related peptidase, is elevated in advanced colorectal cancer and associated with shorter survival. High KLK7 levels in ascites correlate with peritoneal metastasis. In mice, KLK7 overexpression increases metastasis. In vitro, KLK7 enhances cancer cell proliferation, migration, adhesion, and spheroid formation, driving ...
Yosr Z. Haffani +6 more
wiley +1 more source
A Comparison of Outlier Detection Techniques for High-Dimensional Data
International Journal of Computational Intelligence Systems, 2018 Outlier detection is a hot topic in machine learning. With the newly emerging technologies and diverse applications, the interest of outlier detection is increasing greatly.
Xiaodan Xu +3 more
doaj +1 more source
Multi-Level Clustering-Based Outlier’s Detection (MCOD) Using Self-Organizing Maps
Big Data and Cognitive Computing, 2020 Outlier detection is critical in many business applications, as it recognizes unusual behaviours to prevent losses and optimize revenue. For example, illegitimate online transactions can be detected based on its pattern with outlier detection.
Menglu Li, Rasha Kashef, Ahmed Ibrahim
doaj +1 more source
Frontiers in Astronomy and Space Sciences, 2022 Automatic detection of outliers is universally needed when working with scientific datasets, e.g., for cleaning datasets or flagging novel samples to guide instrument acquisition or scientific analysis.
Hannah R. Kerner +8 more
doaj +1 more source
Identification of Outlying Observations with Quantile Regression for Censored Data [PDF]
, 2014 Outlying observations, which significantly deviate from other measurements, may distort the conclusions of data analysis. Therefore, identifying outliers is one of the important problems that should be solved to obtain reliable results.
Cho, HyungJun +2 more
core
FEBS Open Bio, EarlyView.A tri‐culture of iPSC‐derived neurons, astrocytes, and microglia treated with ferroptosis inducers as an Induced ferroptosis model was characterized by scRNA‐seq, cell survival, and cytokine release assays. This analysis revealed diverse microglial transcriptomic changes, indicating that the system captures key aspects of the complex cellular ...
Hongmei Lisa Li +6 more
wiley +1 more source
Outlier Detection and Explanation Method Based on FOLOF Algorithm
EntropyOutlier mining constitutes an essential aspect of modern data analytics, focusing on the identification and interpretation of anomalous observations. Conventional density-based local outlier detection methodologies frequently exhibit limitations due to ...
Lei Bai, Jiasheng Wang, Yu Zhou
doaj +1 more source
Provable Self-Representation Based Outlier Detection in a Union of Subspaces
, 2017 Many computer vision tasks involve processing large amounts of data contaminated by outliers, which need to be detected and rejected. While outlier detection methods based on robust statistics have existed for decades, only recently have methods based on
Robinson, Daniel P. +2 more
core +1 more source
Effect of adjunctive ranitidine for antipsychotic-induced weight gain: A systematic review of randomized placebo-controlled trials [PDF]
, 2017 This study was a meta-analysis of randomized controlled trials (RCTs) of ranitidine as an adjunct for antipsychotic-induced weight gain in patients with schizophrenia.
Chen, Rui +13 more
core +3 more sources
Outlier sums for differential gene expression analysis [PDF]
Biostatistics, 2006 We propose a method for detecting genes that, in a disease group, exhibit unusually high gene expression in some but not all samples. This can be particularly useful in cancer studies, where mutations that can amplify or turn off gene expression often occur in only a minority of samples.
Robert, Tibshirani, Trevor, Hastie
openaire +2 more sources