Integrative machine learning approaches for predicting disease risk using multi-omics data from the UK Biobank

Machine Learning Techniques for the Performance Enhancement of Multiple Classifiers in the Detection of Cardiovascular Disease from PPG Signals

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Machine-learning algorithms for asthma, COPD, and lung cancer risk assessment using circulating microbial extracellular vesicle data and their application to assess dietary effects

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Building machine learning prediction models for well-being using predictors from the exposome and genome in a population cohort

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Reliability of Supervised Machine Learning Using Synthetic Data in Health Care: Model to Preserve Privacy for Data Sharing

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