Clinical stratification improves the diagnostic accuracy of small omics datasets within machine learning and genome-scale metabolic modelling methods

Keyphrases

• Omics Data 100%
• Machine Learning 100%
• Genome-scale Metabolic Model 100%
• Diagnostic Accuracy 100%
• Modeling Method 100%
• Hepatoblastoma 100%
• Clinical Stratification 100%
• Learning Scale 100%
• Omics 66%
• Multi-omics 66%
• Machine Learning Models 66%
• Metabolic Pathway 33%
• Developed Countries 33%
• Classification Accuracy 33%
• Cancer Onset 33%
• Cancer Progression 33%
• Machine Learning Algorithms 33%
• Reaction Pathway 33%
• Cancer Diagnosis 33%
• Gene Pathway 33%
• Potential Biomarkers 33%
• Computer-aided Diagnosis (CADx) 33%
• Clinical Characteristics 33%
• Early Cancer Detection 33%
• Small Dataset 33%
• Diagnostic Classification 33%
• Mechanistic Prediction 33%
• Metabolic Rewiring 33%
• Mechanistic Knowledge 33%
• Rare Cancer 33%
• Cancer Prediction 33%
• Machine Learning Architectures 33%
• Liver Cancer 33%

Immunology and Microbiology

• Multi-Omics 100%
• Metabolism 33%
• Infancy 33%

Biochemistry, Genetics and Molecular Biology

• Tamsulosin 100%
• Metabolic Pathway 16%
• Infancy 16%