Abstract
Biomedical datasets that aim to collect diverse phenotypic and genomic data across large numbers of individuals are plagued by the large fraction of missing data The ability to accurately impute or “fill-in” missing entries in these datasets is critical to a number of downstream applications.
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An, U., Cai, N., Dahl, A., Sankararaman, S. (2022). AutoComplete: Deep Learning-Based Phenotype Imputation for Large-Scale Biomedical Data. In: Pe'er, I. (eds) Research in Computational Molecular Biology. RECOMB 2022. Lecture Notes in Computer Science(), vol 13278. Springer, Cham. https://doi.org/10.1007/978-3-031-04749-7_38
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DOI: https://doi.org/10.1007/978-3-031-04749-7_38
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