AI for Personalized Nutrition

It’s been ages since dieticians started giving personalized advice. However, AI for personalized nutrition is a relatively new topic. In the past few decades, we’ve seen a rise in innovative technologies, apps, and wearable devices for monitoring health.

Nutrition is essential for healthy growth and development. All the body’s major systems such as the immune, nervous, and reproductive rely on proper nutrition for functioning soundly. It even provides the backbone for good cognitive abilities. Thus people with adequate nutrition can terminate the sequence of hunger and poverty. Malnutrition includes both; deficiencies as well as excesses of nutrient intake. Malnutrition sparks off a global economic, social, and medical burden. Hence, this problem needs to be dealt with and using AI for personalized nutrition offers a solution.

The Need of AI for Personalized Nutrition

What is Personalized Nutrition

Personalized nutrition means that nutritional advice and food recommendations should be individualized. The differences in each body’s genetics, microbiome distribution, and metabolism give rise to different nutritional needs and outcomes even when having identical meal plans. Hence it is crucial to consider these factors as well as the person’s lifestyle, height, weight, medical history, and personal eating habits when designing a diet plan.

Benefits of Personalized Nutrition

Acquiring personalized nutrition counseling saves one from pursuing fad diets. Fad diets assist you to lose weight but this may come at the expense of losing important macro and micronutrients. Furthermore, fad diets don’t facilitate the transition from bad to good lifestyle changes causing you to return to your old unhealthy practices once you’ve reached your target weight. Recent studies have proved that personalized diets lead to better health outcomes. One study, revolving around hospitalized patients demonstrated that patients given personalized nutrition care showed better health outcomes when compared to the ones receiving standard hospital food.

Personalized Nutrition based on AI

Introduction to AI in the Field of Nutrition

The omics (metabolomics, genomics, proteomics) data, patient history, and other factors that necessitate personalized nutrition are often complex, diverse, and have a high dimensionality. AI systems, mathematical models, and machine learning classifiers can be used to organize and interpret such large volumes of data. In order to derive meaningful predictions and personalized nutrition tips from such data, the use of AI becomes unquestionable.

How AI Analyzes and Processes Nutritional Data

Decades ago, large data repositories were nothing but data storage houses. With the advent of AI methods, these data homes have become brains that permit knowledge extraction. AI systems first round up all the data originating from different sources. The more abundant and diverse the data is, the more detailed the results of customized nutritional plans will be. The data is inspected for errors and structured. It is then subjected to either supervised or unsupervised learning techniques. Finally, it is analyzed for patterns and derives results that predict different things (predictive analysis) such as the impact of particular nutrients on the propensity to a certain disease.

Before performing nutritional experiments on real people AI can generate synthetic populations of people using clinical data. Clinical trials can be optimized by conducting in silico experiments. The outcome of these trials can be used to review treatment options and the likely effects on health. This way, AI for personalized nutrition offers major advantages.

AI’s Role in Recommending Personalized Diets

AI plays an appreciable role in the creation of tailored nutritional plans. AI applies advanced algorithms to obtain information from vast amounts of patient data about the types of foods that align with an individual’s nutritional demands. This data not only includes patients’ medical history, allergies, and disease risks but also a person’s unique food preferences. It can even recognize the nutritional composition of different foods.

In this way, AI can alter food recipes, to make food more nutritious or less fatty, depending upon what the individual needs but does not force the individual to give up on his/her favorite dishes on the menu. In addition to providing recommendations, AI can monitor your health by tracking your health metrics and providing feedback on how to modify your eating habits or lifestyle to accomplish your health goals.

Examples

Youniq:

This app keeps a record of the user’s microbiome, genomic tests, urine analysis, allergy information, height, weight, etc. The app developers claim their app provides users with more “actionable” options. This app’s algorithm allows it to scan the user’s refrigerator and puts together recipes using what’s available. Youniq can score recipes and keeps people posted on which recipes align with their goals. Each user can dictate their own goals which may include, sleeping better, dealing with a chronic illness, or losing weight.

Calorie Mama:

If you want to know the calorie content of your traditional dishes, but there is no online nutritional information available for the meal you’ve prepared, calorie mama is the app you must have. Image classification technology together with deep learning enables Calorie Mama to recognize all sorts of global cuisines. A research study on food image recognition apps demonstrated that calorie mama’s accuracy ranks among the top performers.

DayTwo:

To create your profile on DayTwo, you need to get your stool sampled and fill out a questionnaire asking for other details. Using this data, DayTwo can make predictions about how a certain food would affect a particular person’s blood glucose. You can eat about anything you want to but DayTwo will recommend you to make a few changes to make it safer for you to consume. For example, a diabetic who loves to eat macaroni and cheese may have to incorporate more proteins. Adding more proteins and fat can tone down the sugar spike.

The future of AI in the field of personalized nutrition seems very promising although there are many modifications and improvements required as of now. It is worth mentioning, however, that the lack of human attributes makes it nearly impossible to imagine the complete replacement of humans with AI.