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Using graph-based ML methods (graph representation learning or geometric deep learning), this interesting analysis identifies which foods, i.e. "hyperfoods", contain ingredients that might work in a similar fashion as medical drugs in beating cancer and other diseases.
Tea and citrus fruits are examples of foods fulfilling both of these conditions: first, they contain multiple anti-cancer drug-like compounds identified by our ML model and confirmed from medical literature, and second, these compounds exert complementary anti-cancer effects.
Besides the aforementioned tea and citruses, cabbage, celery, and sage are rather common, cheap, and broadly available hyperfoods. In a sense, this comes to no surprise, as many of these foods are advocated as healthy choices by nutrition experts and there is overwhelming evidence of their health benefits.
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Enjoyed reading this article. Nice application of machine learning.
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TL;DR
Using graph-based ML methods (graph representation learning or geometric deep learning), this interesting analysis identifies which foods, i.e. "hyperfoods", contain ingredients that might work in a similar fashion as medical drugs in beating cancer and other diseases.
Article Link
https://towardsdatascience.com/hyperfoods-9582e5d9a8e4
Author
Michael Bronstein
Key Takeaways
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Comments/ Questions
Enjoyed reading this article. Nice application of machine learning.
The text was updated successfully, but these errors were encountered: