The suitability of radiomics extracted from 4DCT motion‐compensated reconstruction
Sign Up to like & getrecommendations! Published in 2025 at "Journal of Applied Clinical Medical Physics"
DOI: 10.1002/acm2.70254
Abstract: Abstract Purpose The most appropriate 4DCT image for radiomics analysis remains uncertain, with options including individual respiratory phases and motion‐compensated (MC) reconstructions. This study compares radiomic features derived from MC reconstructions and patient‐specific, 4D phases,… read more here.
Keywords: motion compensated; image; registration algorithms; image type ... See more keywords
Improving Harris hawks optimization algorithm for hyperparameters estimation and feature selection in v‐support vector regression based on opposition‐based learning
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Chemometrics"
DOI: 10.1002/cem.3311
Abstract: Many real problems have been solved by support vector regression, especially v‐support vector regression (v‐SVR), but there are hyperparameters that usually needed to tune. In addition, v‐SVR cannot perform feature selection. Nature‐inspired algorithms have been… read more here.
Keywords: vector regression; feature; feature selection; support vector ... See more keywords
HiBBKA: A Hybrid Method With Resampling and Heuristic Feature Selection for Class‐Imbalanced Data in Chemometrics
Sign Up to like & getrecommendations! Published in 2025 at "Journal of Chemometrics"
DOI: 10.1002/cem.70029
Abstract: In critical domains including medicinal chemistry, biomedicine, metabolomics, and computational toxicology, class imbalance in datasets and poor recognition accuracy for minority classes remain persistent challenges. While previous studies have employed resampling and feature selection techniques… read more here.
Keywords: imbalanced data; rbu smote; feature selection; class ... See more keywords
NCA-GA-SVM: A new two-level feature selection method based on neighborhood component analysis and genetic algorithm in hepatocellular carcinoma (HCC) fatality prognosis.
Sign Up to like & getrecommendations! Published in 2022 at "International journal for numerical methods in biomedical engineering"
DOI: 10.1002/cnm.3599
Abstract: Hepatocellular carcinoma (HCC) is one of the major challenges facing biomedical research. Despite the high lethality, methods to predict mortality for this type of aggressive malignant tumor are insufficient. Machine learning is recognized by many… read more here.
Keywords: hepatocellular carcinoma; feature selection; algorithm;
Optimal channel and frequency band‐based feature selection for motor imagery electroencephalogram classification
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Imaging Systems and Technology"
DOI: 10.1002/ima.22823
Abstract: Common spatial pattern (CSP) is a widely adopted method for electroencephalogram (EEG) feature extraction in brain‐computer interface (BCI) based on motor imagery. Bandpass‐filtering EEG into several subbands related to brain activity tasks is an effective… read more here.
Keywords: optimal channel; feature; channel frequency; feature selection ... See more keywords
Feature selection for high‐dimensional regression via sparse LSSVR based on Lp ‐norm
Sign Up to like & getrecommendations! Published in 2021 at "International Journal of Intelligent Systems"
DOI: 10.1002/int.22334
Abstract: When solving many regression problems, there exist a large number of input features. However, not all features are relevant for current regression, and sometimes, including irrelevant features may deteriorate the learning performance. Therefore, it is… read more here.
Keywords: high dimensional; feature selection; regression; lssvr ... See more keywords
Multiobjective whale optimization algorithm‐based feature selection for intelligent systems
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Intelligent Systems"
DOI: 10.1002/int.22979
Abstract: With regard to large dimensions of contemporary data sets and restricted computational time of intelligent systems, reducing the dimensions of data sets is necessary. Feature selection is a practical way to remove a set of… read more here.
Keywords: whale optimization; algorithm; intelligent systems; feature selection ... See more keywords
Class‐paired Fuzzy SubNETs: A paired variant of the rank‐based network analysis family for feature selection based on protein complexes
Sign Up to like & getrecommendations! Published in 2017 at "PROTEOMICS"
DOI: 10.1002/pmic.201700093
Abstract: Identifying reproducible yet relevant protein features in proteomics data is a major challenge. Analysis at the level of protein complexes can resolve this issue and we have developed a suite of feature‐selection methods collectively referred… read more here.
Keywords: class; analysis; protein; feature selection ... See more keywords
Multilabel feature selection: A comprehensive review and guiding experiments
Sign Up to like & getrecommendations! Published in 2018 at "Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery"
DOI: 10.1002/widm.1240
Abstract: Feature selection has been an important issue in machine learning and data mining, and is unavoidable when confronting with high‐dimensional data. With the advent of multilabel (ML) datasets and their vast applications, feature selection methods… read more here.
Keywords: comprehensive review; selection; feature selection; multilabel feature ... See more keywords
Histologic subtype classification of non-small cell lung cancer using PET/CT images
Sign Up to like & getrecommendations! Published in 2020 at "European Journal of Nuclear Medicine and Molecular Imaging"
DOI: 10.1007/s00259-020-04771-5
Abstract: Purposes To evaluate the capability of PET/CT images for differentiating the histologic subtypes of non-small cell lung cancer (NSCLC) and to identify the optimal model from radiomics-based machine learning/deep learning algorithms. Methods In this study,… read more here.
Keywords: machine; feature selection; pet images; accuracy ... See more keywords
Boosted binary Harris hawks optimizer and feature selection
Sign Up to like & getrecommendations! Published in 2020 at "Engineering with Computers"
DOI: 10.1007/s00366-020-01028-5
Abstract: Feature selection is a required preprocess stage in most of the data mining tasks. This paper presents an improved Harris hawks optimization (HHO) to find high-quality solutions for global optimization and feature selection tasks. This… read more here.
Keywords: feature selection; ihho; selection; hho ... See more keywords