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Found 16 papers, 1 papers with code
ChatDiet: Empowering Personalized Nutrition-Oriented Food Recommender Chatbots through an LLM-Augmented Framework
The personal model leverages causal discovery and inference techniques to assess personalized nutritional effects for a specific user, whereas the population model provides generalized information on food nutritional content.
Knowledge-Infused LLM-Powered Conversational Health Agent: A Case Study for Diabetes Patients
We compare the proposed CHA with GPT4.
Food Recommendation as Language Processing (F-RLP): A Personalized and Contextual Paradigm
State-of-the-art rule-based and classification-based food recommendation systems face significant challenges in becoming practical and useful.
Conversational Health Agents: A Personalized LLM-Powered Agent Framework
openCHA includes an orchestrator to plan and execute actions for gathering information from external sources, essential for formulating responses to user inquiries.
Foundation Metrics for Evaluating Effectiveness of Healthcare Conversations Powered by Generative AI
The purpose of this paper is to explore state-of-the-art LLM-based evaluation metrics that are specifically applicable to the assessment of interactive conversational models in healthcare.
Objective Prediction of Tomorrow's Affect Using Multi-Modal Physiological Data and Personal Chronicles: A Study of Monitoring College Student Well-being in 2020
Results showed that our model was able to predict next-day affect with accuracy comparable to state of the art methods.
Towards Integrative Multi-Modal Personal Health Navigation Systems: Framework and Application
In addition to describing the general framework, we test the PHN system in two experiments within the field of cardiology.
Personal Mental Health Navigator: Harnessing the Power of Data, Personal Models, and Health Cybernetics to Promote Psychological Well-being
Traditionally, the regime of mental healthcare has followed an episodic psychotherapy model wherein patients seek care from a provider through a prescribed treatment plan developed over multiple provider visits.
Personalized Taste and Cuisine Preference Modeling via Images
Using the underlying connection between cuisines and their inherent tastes, we attempt to develop such a profile for an individual based solely on the images of his food.
Food Recommendation: Framework, Existing Solutions and Challenges
A growing proportion of the global population is becoming overweight or obese, leading to various diseases (e. g., diabetes, ischemic heart disease and even cancer) due to unhealthy eating patterns, such as increased intake of food with high energy and high fat.
Flavour Enhanced Food Recommendation
We propose a mechanism to use the features of flavour to enhance the quality of food recommendations.
A Navigational Approach to Health
Lifestyle and environment interacting with our biological machine are primarily responsible for shaping our health and wellbeing.
Human-Computer Interaction
Surface Type Estimation from GPS Tracked Bicycle Activities
Machine learning models such as support vector machines, K-nearest neighbors, and decision trees were used for the classification of the path.
A Survey on Food Computing
This is the first comprehensive survey that targets the study of computing technology for the food area and also offers a collection of research studies and technologies to benefit researchers and practitioners working in different food-related fields.
Computers and Society Multimedia
From Photo Streams to Evolving Situations
Photos are becoming spontaneous, objective, and universal sources of information.
Habits vs Environment: What really causes asthma?
We propose a framework to rank the risk factors from heterogeneous data sources of the two categories.
