115 citations · 157 across the 19 of their papers we have counts for
7 papers · 1 filter
Accuracy and Consistency of LLMs in the Registered Dietitian Exam: The Impact of Prompt Engineering and Knowledge Retrieval
Iman Azimi, Mohan Qi, Li Wang +2
Large language models (LLMs) are fundamentally transforming human-facing applications in the health and well-being domains: boosting patient engagement, accelerating clinical decis…
Graph-Augmented LLMs for Personalized Health Insights: A Case Study in Sleep Analysis
Ajan Subramanian, Zhongqi Yang, Iman Azimi +1
Health monitoring systems have revolutionized modern healthcare by enabling the continuous capture of physiological and behavioral data, essential for preventive measures and early…
Empathy Through Multimodality in Conversational Interfaces
Mahyar Abbasian, Iman Azimi, Mohammad Feli +2
Agents represent one of the most emerging applications of Large Language Models (LLMs) and Generative AI, with their effectiveness hinging on multimodal capabilities to navigate co…
ALCM: Autonomous LLM-Augmented Causal Discovery Framework
Elahe Khatibi, Mahyar Abbasian, Zhongqi Yang +2
To perform effective causal inference in high-dimensional datasets, initiating the process with causal discovery is imperative, wherein a causal graph is generated based on observa…
ChatDiet: Empowering Personalized Nutrition-Oriented Food Recommender Chatbots through an LLM-Augmented Framework
Zhongqi Yang, Elahe Khatibi, Nitish Nagesh +4
The profound impact of food on health necessitates advanced nutrition-oriented food recommendation services. Conventional methods often lack the crucial elements of personalization…
Knowledge-Infused LLM-Powered Conversational Health Agent: A Case Study for Diabetes Patients
Mahyar Abbasian, Zhongqi Yang, Elahe Khatibi +5
Effective diabetes management is crucial for maintaining health in diabetic patients. Large Language Models (LLMs) have opened new avenues for diabetes management, facilitating the…
Food Recommendation as Language Processing (F-RLP): A Personalized and Contextual Paradigm
Ali Rostami, Ramesh Jain, Amir M. Rahmani
State-of-the-art rule-based and classification-based food recommendation systems face significant challenges in becoming practical and useful. This difficulty arises primarily beca…