Abstract: A system and method for up-to-date nutrient database management and nutrient assessment with personalized feedback was created by applying artificial intelligence and machine learning algorithms. This system and method allow for the collection of food intake information, generation and storage of new food records with nutritional data and portions, aggregation of complete micronutrient and macronutrient data with real-time feedback to accurately and efficiently assess nutrient intake when compared to nutrient goals.

Abstract: A system and digital health platform that allows a healthcare provider to automate the delivery of medical nutrition therapy. Following the nutrition care process, the system obtains the patient's medical information and determines appropriate nutrition diagnosis, nutrition therapies, and what data should be collected and monitored for each patient. The system is used by registered dietitian nutritionists or other healthcare providers. Based on the patient's nutrition assessment, a frequency of interactions with a medical provider is identified for optimal outcomes. Using identified monitoring tools, patients are monitored for changes in their condition and appropriate nutrition interventions are updated based on these changes. The tool facilitates the evolution of nutrition research by data analytics regarding intervention, patient data, and outcome data.