Meal Planning for Alzheimer's Disease Using an Ontology-Assisted Multiple Criteria Decision-Making Approach

Abstract

As healthy diets and nutrition are crucial for people with Alzheimer's disease (AD), caregivers of patients with AD need to provide a balanced diet with the correct nutrients to boost the health and well-being of patients. However, this is challenging as they are likely to suffer from aging-related problems (such as teeth or gum problems) that make eating more uncomfortable; the planners, who are usually patients' family members, generally face high pressure, a busy schedule, and little experience. To help unprofessional caregivers of AD plan meals with the right nutrition and flavors, in this paper, the authors propose a meal planning mechanism that uses a multiple criteria decision-making approach to integrate various factors that affect a caregiver's choice of meals for AD patients. Ontology-based knowledge has been used to model personal preferences and characteristics and customize general diet recommendations. Case studies have demonstrated the feasibility and usability of the proposed approach.

Delighting Palates with AI: Reinforcement Learning’s Triumph in Crafting Personalized Meal Plans with High User Acceptance

“…The development of personalized meal planning systems has been a subject of considerable interest across various fields, encompassing nutrition science, computer science, and human-computer interaction [1,18,19]. This section reviews the diverse methodologies that have been employed in the quest for effective meal-planning solutions, ranging from rule-based systems to advanced machine learning (ML) techniques.…”