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848 related items for PubMed ID: 31416551

  • 1. C-HMOSHSSA: Gene selection for cancer classification using multi-objective meta-heuristic and machine learning methods.
    Sharma A, Rani R.
    Comput Methods Programs Biomed; 2019 Sep; 178():219-235. PubMed ID: 31416551
    [Abstract] [Full Text] [Related]

  • 2. An Innovative Excited-ACS-IDGWO Algorithm for Optimal Biomedical Data Feature Selection.
    Segera D, Mbuthia M, Nyete A.
    Biomed Res Int; 2020 Sep; 2020():8506365. PubMed ID: 32908920
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  • 3. The feature selection bias problem in relation to high-dimensional gene data.
    Krawczuk J, Łukaszuk T.
    Artif Intell Med; 2016 Jan; 66():63-71. PubMed ID: 26674595
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  • 4. Cancer Feature Selection and Classification Using a Binary Quantum-Behaved Particle Swarm Optimization and Support Vector Machine.
    Xi M, Sun J, Liu L, Fan F, Wu X.
    Comput Math Methods Med; 2016 Jan; 2016():3572705. PubMed ID: 27642363
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  • 5. A centroid-based gene selection method for microarray data classification.
    Guo S, Guo D, Chen L, Jiang Q.
    J Theor Biol; 2016 Jul 07; 400():32-41. PubMed ID: 27056739
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  • 6. A novel gene selection algorithm for cancer classification using microarray datasets.
    Alanni R, Hou J, Azzawi H, Xiang Y.
    BMC Med Genomics; 2019 Jan 15; 12(1):10. PubMed ID: 30646919
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  • 7. Two-stage feature selection for classification of gene expression data based on an improved Salp Swarm Algorithm.
    Qin X, Zhang S, Yin D, Chen D, Dong X.
    Math Biosci Eng; 2022 Sep 19; 19(12):13747-13781. PubMed ID: 36654066
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  • 8. Hybrid Feature Selection Algorithm mRMR-ICA for Cancer Classification from Microarray Gene Expression Data.
    Wang S, Kong W, Aorigele, Deng J, Gao S, Zeng W.
    Comb Chem High Throughput Screen; 2018 Sep 19; 21(6):420-430. PubMed ID: 29852866
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  • 9. Improving feature selection performance for classification of gene expression data using Harris Hawks optimizer with variable neighborhood learning.
    Qu C, Zhang L, Li J, Deng F, Tang Y, Zeng X, Peng X.
    Brief Bioinform; 2021 Sep 02; 22(5):. PubMed ID: 33876181
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  • 10. Reviewing ensemble classification methods in breast cancer.
    Hosni M, Abnane I, Idri A, Carrillo de Gea JM, Fernández Alemán JL.
    Comput Methods Programs Biomed; 2019 Aug 02; 177():89-112. PubMed ID: 31319964
    [Abstract] [Full Text] [Related]

  • 11. Development of a two-stage gene selection method that incorporates a novel hybrid approach using the cuckoo optimization algorithm and harmony search for cancer classification.
    Elyasigomari V, Lee DA, Screen HR, Shaheed MH.
    J Biomed Inform; 2017 Mar 02; 67():11-20. PubMed ID: 28163197
    [Abstract] [Full Text] [Related]

  • 12. New algorithms for multi-class cancer diagnosis using tumor gene expression signatures.
    Bagirov AM, Ferguson B, Ivkovic S, Saunders G, Yearwood J.
    Bioinformatics; 2003 Sep 22; 19(14):1800-7. PubMed ID: 14512351
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  • 13. An ensemble correlation-based gene selection algorithm for cancer classification with gene expression data.
    Piao Y, Piao M, Park K, Ryu KH.
    Bioinformatics; 2012 Dec 15; 28(24):3306-15. PubMed ID: 23060613
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  • 14. A hybrid gene selection algorithm based on interaction information for microarray-based cancer classification.
    Nakariyakul S.
    PLoS One; 2019 Dec 15; 14(2):e0212333. PubMed ID: 30768654
    [Abstract] [Full Text] [Related]

  • 15. A class imbalance-aware Relief algorithm for the classification of tumors using microarray gene expression data.
    He Y, Zhou J, Lin Y, Zhu T.
    Comput Biol Chem; 2019 Jun 15; 80():121-127. PubMed ID: 30947070
    [Abstract] [Full Text] [Related]

  • 16. An Integrated Feature Selection Algorithm for Cancer Classification using Gene Expression Data.
    Ahmed S, Kabir M, Ali Z, Arif M, Ali F, Yu DJ.
    Comb Chem High Throughput Screen; 2018 Jun 15; 21(9):631-645. PubMed ID: 30569852
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  • 17. Multi-Swarm Algorithm for Extreme Learning Machine Optimization.
    Bacanin N, Stoean C, Zivkovic M, Jovanovic D, Antonijevic M, Mladenovic D.
    Sensors (Basel); 2022 May 31; 22(11):. PubMed ID: 35684824
    [Abstract] [Full Text] [Related]

  • 18. A fast gene selection method for multi-cancer classification using multiple support vector data description.
    Cao J, Zhang L, Wang B, Li F, Yang J.
    J Biomed Inform; 2015 Feb 31; 53():381-9. PubMed ID: 25549938
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  • 19. Genetic Bee Colony (GBC) algorithm: A new gene selection method for microarray cancer classification.
    Alshamlan HM, Badr GH, Alohali YA.
    Comput Biol Chem; 2015 Jun 31; 56():49-60. PubMed ID: 25880524
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  • 20. A granular computing approach to gene selection.
    Sun L, Xu J.
    Biomed Mater Eng; 2014 Jun 31; 24(1):1307-14. PubMed ID: 24212026
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