Results 31 to 40 of about 1,645,629 (287)
A neural network for mining large volumes of time series data [PDF]
, 2005 Efficiently mining large volumes of time series data is amongst the most challenging problems that are fundamental in many fields such as industrial process monitoring, medical data analysis and business forecasting.
Austin, J., Liang, B.
core +1 more source
An Improved Heteroscedastic Modeling Method for Chest X-ray Image Classification with Noisy Labels
Algorithms, 2023 Chest X-ray image classification suffers from the high inter-similarity in appearance that is vulnerable to noisy labels. The data-dependent and heteroscedastic characteristic label noise make chest X-ray image classification more challenging. To address
Qingji Guan, Qinrun Chen, Yaping Huang
doaj +1 more source
A comprehensive evaluation of module detection methods for gene expression data
Nature Communications, 2018 Modules composed of groups of genes with similar expression profiles tend to be functionally related and co-regulated. Here, Saelens et al evaluate the performance of 42 computational methods and provide practical guidelines for module detection in gene ...
Wouter Saelens +2 more
doaj +1 more source
Data Mining in Electronic Commerce
, 2006 Modern business is rushing toward e-commerce. If the transition is done properly, it enables better management, new services, lower transaction costs and better customer relations.
Banks, David L., Said, Yasmin H.
core +1 more source
Set-oriented data mining in relational databases [PDF]
, 1995 Data mining is an important real-life application for businesses. It is critical to find efficient ways of mining large data sets. In order to benefit from the experience with relational databases, a set-oriented approach to mining data is needed.
Houtsma, Maurice, Swami, Arun
core +4 more sources
, 2013 During the years of the Information Age, technological advances in the computers, satellites, data transfer, optics, and digital storage has led to the collection of an immense mass of data on everything from business to astronomy, counting on the power of digital computing to sort through the amalgam of information and generate meaning from the data ...
Drachen, Anders +4 more
openaire +3 more sources
Radiogenomic-based prediction of genetic alterations in oncogenic signaling pathways in lung cancer
Egyptian Journal of Medical Human GeneticsRationale and objectives Lung adenocarcinoma, a type of non-small cell lung cancer (NSCLC), originates from the peripheral lung tissue and is the most prevalent histologic subtype, constituting around 40% of cases.
Priyadharshini Jayachandran +2 more
doaj +1 more source
Molecular Oncology, EarlyView.Glioma cells mainly express the endothelin receptor EDNRB, while EDNRA is restricted to a perivascular tumor subpopulation. Endothelin signaling reduces glioma cell proliferation while promoting migration and a proneural‐to‐mesenchymal transition associated with poor prognosis. This pathway activates Ca2+, K+, ERK, and STAT3 signalings and is regulated
Donovan Pineau +36 more
wiley +1 more source
Product-Driven Data Mining [PDF]
, 2003 Manifold Data Mining has developed innovative demographic and household spending pattern databases for six-digit postal codes in Canada. Their collection of information consists of both demographic and expenditure variables which are expressed through ...
Bohun, C. Sean
core
Molecular Oncology, EarlyView.CIN85 is highly expressed in osteosarcoma, particularly in metastatic lesions. Its overexpression increases cell migration and Matrigel invasion, while silencing CIN85 suppresses these behaviors. Transcriptome analysis shows that CIN85 regulates MMP2, COL3A1, and Akt/mTOR signaling. Targeting these pathways reverses CIN85‐induced motility, highlighting
Iryna Horak +10 more
wiley +1 more source