115 citations · 151 across the 11 of their papers we have counts for
11 papers
A knowledge-guided agentic framework for mitigating patient-context ambiguity in health queries
Mahyar Abbasian, Saba A. Farahani, Arshia Ilaty +3
Patients often submit short, underspecified queries to healthcare chatbots that lack the patient-specific information needed to determine an appropriate response. Although these qu…
T2D-Bench: Evidence-Gated Evaluation of LLM Outputs for Type 2 Diabetes Using a Multi-Layer Clinical-Lifestyle Knowledge Graph
Saba A. Farahani, Hung Cao, Ramesh Jain +1
Large language models (LLMs) can produce clinically fluent recommendations for type 2 diabetes while failing to satisfy guideline constraints or explicitly justify lifestyle-relate…
Personal Care Utility: Health as Everyday Infrastructure
Mahyar Abbasian, Elahe Khatibi, Saba A. Farahani +5
Healthcare is essential, expert, and episodic by design - built around the roughly one hour per year a person spends with a clinician. The 8,759 hours outside clinical settings, wh…
PerCaM-Health: Personalized Dynamic Causal Graphs for Healthcare Reasoning
Elahe Khatibi, Ziyu Wang, Saba A. Farahani +4
Personalized healthcare decisions require reasoning about how physiological and behavioral variables influence an individual patient over time. Existing temporal causal discovery m…
Personal Care Utility (PCU): Building the Health Infrastructure for Everyday Insight and Guidance
Mahyar Abbasian, Ramesh Jain
Building on decades of success in digital infrastructure and biomedical innovation, we propose the Personal Care Utility (PCU) - a cybernetic system for lifelong health guidance. P…
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…
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…
Conversational Health Agents: A Personalized LLM-Powered Agent Framework
Mahyar Abbasian, Iman Azimi, Amir M. Rahmani +1
Conversational Health Agents (CHAs) are interactive systems that provide healthcare services, such as assistance and diagnosis. Current CHAs, especially those utilizing Large Langu…
Foundation Metrics for Evaluating Effectiveness of Healthcare Conversations Powered by Generative AI
Mahyar Abbasian, Elahe Khatibi, Iman Azimi +11
Generative Artificial Intelligence is set to revolutionize healthcare delivery by transforming traditional patient care into a more personalized, efficient, and proactive process.…