stdClass Object
(
    [id] => 14025
    [paper_index] => 202409-01-018368
    [title] => GENOMICA AI- ENHANCING GENETIC MARKER IDENTIFICATION THROUGH MACHINE LEARNING
    [description] => 
    [author] => Mr. Sudeep M S, Mr. Veeresh A C, Mrs. Anitha J
    [googlescholar] => 
    [doi] => 
    [year] => 2024
    [month] => September
    [volume] => 10
    [issue] => 9
    [file] => fm/jpanel/upload/2024/September/202409-01-018368.pdf
    [abstract] => The identification of genetic markers such as single nucleotide polymorphisms (SNPs) plays a critical role in understanding disease susceptibility and guiding personalized medicine. Recent advances in machine learning (ML) have provided new methods to address the complexities of genetic data. This paper introduces a novel ensemble learning technique that integrates attention-based neural networks with traditional random forest algorithms to enhance the identification of SNPs linked to disease outcomes. Using a benchmark dataset of genome-wide association studies (GWAS), we demonstrate how the proposed method improves prediction accuracy and model interpretability, thereby offering potential applications in clinical genomics.
    [keywords] => 
    [doj] => 2024-09-25
    [hit] => 
    [status] => 
    [award_status] => P
    [orderr] => 72
    [journal_id] => 1
    [googlesearch_link] => 
    [edit_on] => 
    [is_status] => 1
    [journalname] => EPRA International Journal of Multidisciplinary Research (IJMR)
    [short_code] => IJMR
    [eissn] =>  2455-3662 (Online)
    [pissn] => - --
    [home_page_wrapper] => images/products_image/11.IJMR.png
)
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