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Journal Abstract Search

442 related items for PubMed ID: 25961028

  • 21. A multiple kernel support vector machine scheme for feature selection and rule extraction from gene expression data of cancer tissue.
    Chen Z, Li J, Wei L.
    Artif Intell Med; 2007 Oct; 41(2):161-75. PubMed ID: 17851055
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  • 22. Hybrid genetic algorithm-neural network: feature extraction for unpreprocessed microarray data.
    Tong DL, Schierz AC.
    Artif Intell Med; 2011 Sep; 53(1):47-56. PubMed ID: 21775110
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  • 24. Enhancing the prediction of IDC breast cancer staging from gene expression profiles using hybrid feature selection methods and deep learning architecture.
    Kishore A, Venkataramana L, Prasad DVV, Mohan A, Jha B.
    Med Biol Eng Comput; 2023 Nov; 61(11):2895-2919. PubMed ID: 37530887
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  • 25. Whale optimized mixed kernel function of support vector machine for colorectal cancer diagnosis.
    Zhao D, Liu H, Zheng Y, He Y, Lu D, Lyu C.
    J Biomed Inform; 2019 Apr; 92():103124. PubMed ID: 30796977
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  • 27. 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
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  • 28. A novel and innovative cancer classification framework through a consecutive utilization of hybrid feature selection.
    Mahto R, Ahmed SU, Rahman RU, Aziz RM, Roy P, Mallik S, Li A, Shah MA.
    BMC Bioinformatics; 2023 Dec 15; 24(1):479. PubMed ID: 38102551
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  • 29. An integrated algorithm for gene selection and classification applied to microarray data of ovarian cancer.
    Lee ZJ.
    Artif Intell Med; 2008 Jan 15; 42(1):81-93. PubMed ID: 18006289
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  • 30. Gene selection for cancer classification with the help of bees.
    Moosa JM, Shakur R, Kaykobad M, Rahman MS.
    BMC Med Genomics; 2016 Aug 10; 9 Suppl 2(Suppl 2):47. PubMed ID: 27510562
    [Abstract] [Full Text] [Related]

  • 31. 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 10; 53():381-9. PubMed ID: 25549938
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  • 32. A TRIZ-inspired bat algorithm for gene selection in cancer classification.
    Al-Betar MA, Alomari OA, Abu-Romman SM.
    Genomics; 2020 Jan 10; 112(1):114-126. PubMed ID: 31676302
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  • 37. Multiple sequence alignment using multi-objective based bacterial foraging optimization algorithm.
    Rani RR, Ramyachitra D.
    Biosystems; 2016 Dec 10; 150():177-189. PubMed ID: 27784624
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  • 38. Genetic algorithm-based feature selection with manifold learning for cancer classification using microarray data.
    Wang Z, Zhou Y, Takagi T, Song J, Tian YS, Shibuya T.
    BMC Bioinformatics; 2023 Apr 08; 24(1):139. PubMed ID: 37031189
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  • 39. Optimizing cancer diagnosis: A hybrid approach of genetic operators and Sinh Cosh Optimizer for tumor identification and feature gene selection.
    Emam MM, Houssein EH, Samee NA, Alkhalifa AK, Hosney ME.
    Comput Biol Med; 2024 Sep 08; 180():108984. PubMed ID: 39128177
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