Transformational power of AI-driven technology in nutritional health

Objective:   AI technology is revolutionizing nutritional healthcare through applications focused on five fundamental drivers:  personalization, precision, prediction, proactive, and prevention.   This review explores leading digital AI trends predicated on the five drivers, while examining existing and emerging tools supporting these trends within the transformational landscape.  Analysis of the solutions and the importance of AI in the advancement of nutritional healthcare are performed.

Methods:   The leading nutrition-related AI technology trends evaluated for the purposes of this study include:

1. Generation of personalized nutritional recommendations via ML algorithms using patient profiling (e.g., symptoms, medications, preferences), labs (blood, urine, saliva, genetics, microbiome), and wearable biomarker monitors.


2. Delivery of tailored recipes and meal plans based on patient-specific symptoms and other variables.


3. Creation of personalized shopping lists and restaurant recommendations via ML algorithms.


4. Prediction of physiological responses to specific foods with ML-generated preventive diets.


5. Development of diet supplementation based on ML-predicted drug-nutrient interactions.


6. Implementation of food image recognition and ingestion monitoring tools to simplify food logging and dietary assessment protocols.


7. Utilization of ChatGPT to perform research, develop content and/or function as an adjunct nutritional coach.


8. Use of chatbots to deliver ML-generated proactive reminders and messages.