Can an algorithm help us eat better?

That’s the question I’ll be discussing with my guest today, Professor Eran Segal, a professor at the Department of Computer Science and Applied Mathematics at the Weizmann Institute of Science (WIS), heading a lab with computational biologists and experimental scientists who have extensive experience in machine learning and computational biology allowing them to decipher how something as complex as diet, interacts with something infinitely more complex … us.

Our genes, microbes, and unique environments are obviously going to impact how we respond to different foods and diets and Professor Segal is on a mission to figure out how we can use his favouroite tool, algorithms, to help us eat according to our unique biology.

We first dive into our unique blood sugar responses and their seminal paper published in Cell that demonstrated the drastically different responses we all have and potential reasons why.

How we calculate GI and GL index and what’s wrong these, what happens when we have high blood sugar excursions (after a high refined carb meal for example) and the dangers of gameifying our diet too much.

Plus we look into the future with the Human Phenotype Project, the role of faecal transplants and I invite Professor to give us a snapshot of how we practice nutritional self-care in the future with all the ‘omics’.

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