Results 71 to 80 of about 7,151,646 (328)
Elite Bases Regression: A Real-time Algorithm for Symbolic Regression
Symbolic regression is an important but challenging research topic in data mining. It can detect the underlying mathematical models. Genetic programming (GP) is one of the most popular methods for symbolic regression. However, its convergence speed might
Chen, Chen+2 more
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Cell‐free DNA aneuploidy score as a dynamic early response marker in prostate cancer
mFast‐SeqS‐based genome‐wide aneuploidy scores are concordant with aneuploidy scores obtained by whole genome sequencing from tumor tissue and can predict response to ARSI treatment at baseline and, at an early time point, to ARSI and taxanes. This assay can be easily performed at low cost and requires little input of cfDNA. Cell‐free circulating tumor
Khrystany T. Isebia+17 more
wiley +1 more source
Machine-Learning Models for Sales Time Series Forecasting
In this paper, we study the usage of machine-learning models for sales predictive analytics. The main goal of this paper is to consider main approaches and case studies of using machine learning for sales forecasting.
Bohdan M. Pavlyshenko
doaj +1 more source
Epithelial–mesenchymal transition (EMT) and tumor‐infiltrating lymphocytes (TILs) are associated with early breast cancer response to neoadjuvant chemotherapy (NAC). This study evaluated EMT and TIL shifts, with immunofluorescence and RNA sequencing, at diagnosis and in residual tumors as potential biomarkers associated with treatment response.
Françoise Derouane+16 more
wiley +1 more source
Adverse prognosis gene expression patterns in metastatic castration‐resistant prostate cancer
We aggregated a cohort of 1012 mCRPC tissue samples from 769 patients and investigated the association of gene expression‐based pathways with clinical outcomes. Loss of AR signaling, high proliferation, and a glycolytic phenotype were independently prognostic for poor outcomes, and an adverse transcriptional feature score incorporating these pathways ...
Marina N. Sharifi+26 more
wiley +1 more source
Functional additive regression
We suggest a new method, called Functional Additive Regression, or FAR, for efficiently performing high-dimensional functional regression. FAR extends the usual linear regression model involving a functional predictor, $X(t)$, and a scalar response, $Y$,
Fan, Yingying+2 more
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Elevated level of cholesterol is positively correlated to prostate cancer development and disease severity. Cholesterol‐lowering drugs, such as statins, are demonstrated to inhibit prostate cancer. VNPP433‐3β interrupts multiple signaling and metabolic pathways, including cholesterol biosynthesis, AR‐mediated transcription of several oncogenes, mRNA 5′
Retheesh S. Thankan+10 more
wiley +1 more source
Bayesian Compressed Regression [PDF]
As an alternative to variable selection or shrinkage in high dimensional regression, we propose to randomly compress the predictors prior to analysis. This dramatically reduces storage and computational bottlenecks, performing well when the predictors ...
Dunson, David B., Guhaniyogi, Rajarshi
core
Modern technologies are producing a wealth of data with complex structures. For instance, in two-dimensional digital imaging, flow cytometry, and electroencephalography, matrix type covariates frequently arise when measurements are obtained for each ...
Li, Lexin, Zhou, Hua
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Low expression of five purine metabolism‐related genes (ADSL, APRT, ADCY3, NME3, NME6) was correlated with poor survival in colorectal cancer. Immunohistochemistry analysis showed that low NME3 (early stage) and low ADSL/NME6 (late stage) levels were associated with high risk.
Sungyeon Kim+8 more
wiley +1 more source