A collection of small-sample, high-dimensional microarray data sets to assess machine-learning algorithms and models.
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Updated
Jan 10, 2016 - R
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colon-cancer
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scikit-learn clinical-trials lasso-regression colon-cancer blacklisting-filter unique-molecular-identifiers fragmentomics rectal-cancer limit-of-detection colon-adenoma rectal-adenoma detect-recurrence predict-relapse ultra-deep-sequencing tumor-agnostic-approach error-rates mutation-score dna-fragmentation-patterns detection-error-rates sensitivity-specificity
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Nov 26, 2023 - R
deep-learning lung-cancer ovarian-cancer whole-genome-sequencing breast-cancer colon-cancer pancreatic-cancer early-detection fragmentomics fragmentation-patterns rectal-cancer gastric-cancer colon-adenoma rectal-adenoma bile-duct-cancer duodenal-cancer sub-clinical-disease dna-fragment-length identify-disease-stage early-detection-of-disease
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Updated
Nov 26, 2023 - R
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