Abstract
In clinical research big data are particularly observed with genetic studies of the relationships between the genome and clinical outcomes like metabolics and more. With genome wide research we have to take into account the presence of 250.0000 genes in every human cell, and 2000 nucleic acids in every gene. This chapter is to address whether sparse canonical correlation analysis performs better in identifying predictor-outcome relationships than other analytic methods so far.
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Cleophas, T.J., Zwinderman, A.H. (2020). Sparse Canonical Correlation Analysis. In: Machine Learning in Medicine – A Complete Overview. Springer, Cham. https://doi.org/10.1007/978-3-030-33970-8_53
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DOI: https://doi.org/10.1007/978-3-030-33970-8_53
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Publisher Name: Springer, Cham
Print ISBN: 978-3-030-33969-2
Online ISBN: 978-3-030-33970-8
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