EnGRaiN: a supervised ensemble learning method for recovery of large-scale gene regulatory networks
Sign Up to like & getrecommendations! Published in 2022 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btab829
Abstract: MOTIVATION Reconstruction of genome-scale networks from gene expression data is an actively studied problem. A wide range of methods that differ between the types of interactions they uncover with varying trade-offs between sensitivity and specificity… read more here.
Keywords: engrain supervised; method recovery; learning method; supervised ensemble ... See more keywords
Stratified Feature Sampling for Semi-Supervised Ensemble Clustering
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2939581
Abstract: Ensemble Clustering (EC), which seeks to generate a consensus clustering by integrating multiple base clusterings, has attracted increasing attentions. However, traditional EC methods typically have three main limitations: (1) High dimensional data present a huge… read more here.
Keywords: stratified feature; semi supervised; supervised ensemble; ensemble clustering ... See more keywords
Automatic Segmentation of Novel Coronavirus Pneumonia Lesions in CT Images Utilizing Deep-Supervised Ensemble Learning Network
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Medicine"
DOI: 10.3389/fmed.2021.755309
Abstract: Background: The novel coronavirus disease 2019 (COVID-19) has been spread widely in the world, causing a huge threat to the living environment of people. Objective: Under CT imaging, the structure features of COVID-19 lesions are… read more here.
Keywords: ensemble learning; learning; segmentation; supervised ensemble ... See more keywords