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Heterogeneous multiple kernel learning for breast cancer outcome evaluation
2020
BMC Bioinformatics
Breast cancer is one of the common kinds of cancer among women, and it ranks second among all cancers in terms of incidence, after lung cancer. Therefore, it is of great necessity to study the detection methods of breast cancer. Recent research has focused on using gene expression data to predict outcomes, and kernel methods have received a lot of attention regarding the cancer outcome evaluation. However, selecting the appropriate kernels and their parameters still needs further investigation.
doi:10.1186/s12859-020-3483-0
pmid:32326887
pmcid:PMC7181520
fatcat:yjw4mcg5gjd5hce3zvueoodmey