Nutrition Meets Artificial Intelligence (Part II)
Many companies are in the experimental phase of exploring machine learning’s extensive capabilities in relation to improving existing applications. One of these companies is FitGenie.
FitGenie
The app includes features, such as meal planning where it applies a genetic algorithm to “create an optimal meal plan that meets the user’s nutrition targets as well as their [dietary] preferences”, as Osayande put it.
Some other nutrition studies and applications use deep learning to process photos of food taken by the participant to accurately determine what they are eating to avoid manually logging data. For example, the application Ava.
AVA
Ava provides nutrition and personalized coaching based on chronic conditions related to a person’s diet and weight goals.
So let’s dig a little deeper on how we would create this personalized diet…
To implement these methods into the public, numerous companies have been advertising a fairly new science called “nutrigenomics”.
Nutrigenomics: the scientific study of the interaction of nutrition and genes, especially with regard to the prevention or treatment of disease. — Oxford Dictionary
Combining nutrigenomics and artificial intelligence is the key to personalized nutrition.
- It requires filtering an inordinate amount of data. Billions of pieces of data about each person taking into account all of the aspects of that person’s lifestyle — health, anatomy, family history, physiology, environment, medical conditions, medication.
- But, in order to get more accurate results in the future, glucose levels and other anthropometrics, such as heart rate and blood pressure responses, should be analyzed using machine learning to see what drives participants’ responses to specific foods.
Amidst the technologies we have today, we can do this. We are able to pull multiple types of data from devices, such as health apps and smartwatches. For example, Apple on its own has an extensive amount of data from Apple watches, iPhone applications, and even Apple computers. All of this makes customized nutrition very feasible.
With machine learning, we could all have our own personalized virtual health coaches in a couple years. AI personalized diets is the beginning of an exciting new era.
