Machine learning with the TCGA-HNSC dataset: improving usability by addressing inconsistency, sparsity, and high-dimensionality - Rendleman, Michael C.; Buatti, John M.; Braun, Terry A.; Smith, Brian J.; Nwakama, Chibuzo; Beichel, Reinhard R.; Brown, Bart; Casavant, Thomas L. (BMC bioinformatics, 2019)
Keywords: Algorithms; Area Under Curve; Artificial intelligence; Bioinformatics; Biological activity; Biological markers; Biomarkers; Biomedical and Life Sciences; Cancer; Cancer therapies; Carcinoma; CAT scans; Cell death; Classifiers; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Consortia; Data analysis; Databases, Genetic; Datasets; Decision support; Deoxyribonucleic acid; Diagnosis; Dimensionality reduction; DNA; DNA methylation; Evaluation; Gene expression; Gene Ontology; Gene ontology enrichment analysis; Genes; Genetic aspects; Genetic research; Genetic transformation; Head & neck cancer; Head and neck cancer; hnscc; Human papillomavirus; Humans; Information management; Knowledge-based analysis; Learning algorithms; Life Sciences; Machine Learning; Medical prognosis; Microarrays; Novels; Oncology; Ontology; Patients; Precision medicine; Principal Component Analysis; Principal components analysis; Radiomics; Research Article; Ribonucleic acid; RNA; RNA, Neoplasm - genetics; RNA, Neoplasm - metabolism; Sparsity; Squamous cell carcinoma; Squamous Cell Carcinoma of Head and Neck - genetics; tcga; Technology application; Variables; United States; hnscc; Dimensionality reduction; Unsupervised transformation; Gene ontology enrichment analysis; Machine learning; tcga; Decision support