Osprey-Optimized Support Vector Machine-Based Colorectal Cancer Diagnosis for Handling Sample Imbalance Problem in Microarray Technique
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-1724-8_60
Reference12 articles.
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2. Kim D, Cho KH (2023) Hidden patterns of gene expression provide prognostic insight for colorectal cancer. Cancer Gene Ther 30(1):11–21
3. Khameneh SC, Razi S, Shamdani S, Uzan G, Naserian S (2022) Weighted correlation network analysis revealed novel long non-coding RNAs for colorectal cancer. Sci Rep 12(1):2990
4. Toolabi N, Daliri FS, Mokhlesi A, Talkhabi M (2022) Identification of key regulators associated with colon cancer prognosis and pathogenesis. J Cell Commun Signal 1–13
5. Rahman J, Ahammed B, Abedin M, Suri HS, Biswas M, El-Baz A, Suri JS (2020) Statistical characterization and classification of colon microarray gene expression data using multiple machine learning paradigms. In: Cognitive informatics, computer modelling, and cognitive science, pp 273–317. Academic Press
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