This presentation propose an extended framework of personalised medicine, including lifestyle preference and family connectivity. It will start with a recent review of personalized medicine, on its medical and scientific perspectives, data science perspectives, bioethical perspectives, and public perceptions. It will then overview the statistical learning methods for integrated Omics. Based on these reviews, the presenter propose a health-care framework of combining personalized medicine information, lifestyle preference measures and family connectivity measures. Simulations are used to generate case scenarios for the illustrations of potential usages under this framework.
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