How can people effectively integrate data from genomics, metabolomics and microbiomics in individualized treatment of cardiovascular disease to achieve more accurate disease prediction and treatment plans ？
This is just a personal opinion:
Direct multiomics integration for "people" is very difficult. But "AI" has a good potential to do it effectively. What "people" can do is to train AI more efficiently. For this we need to significantly improve the quality of the data we acquire and feed to AI. It is particularly important for metabolomics data, but also there is room for improvement in genomics as well. We also need to have much larger sample size, longitudinal studies, and overall better designed experiments that will be more coordinated between multiple research groups. Realistically speaking it is a great challenge when working with people.
Its really great challenge for integrating genomics, metabolomics and microbiomics to predict cardiovascular disease but we can integrate metabolomics to mcrobiomics by data gathered by AI. genomics is little bit tough task
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