115 citations · 183 across the 18 of their papers we have counts for
19 papers
Explainable Prediction from Mobile Sensing Data through LLM-guided Concept Integration
Yuning Wang, Iman Azimi, Amir M. Rahmani +1
Mobile sensing enables longitudinal monitoring of behavioral and physiological patterns in everyday settings. However, accurate prediction remains challenging in small-cohort healt…
Personalized Digital Health Modeling with Adaptive Support Users
Zhongqi Yang, Mahkameh Rasouli, Neda Mohseni +3
Personalized models are essential in digital health because individuals exhibit substantial physiological and behavioral heterogeneity. Yet personalization is limited by scarce and…
TransECG: Leveraging Transformers for Explainable ECG Re-identification Risk Analysis
Ziyu Wang, Elahe Khatibi, Kianoosh Kazemi +4
Electrocardiogram (ECG) signals are widely shared across multiple clinical applications for diagnosis, health monitoring, and biometric authentication. While valuable for healthcar…
Multimodal Sleep Stage and Sleep Apnea Classification Using Vision Transformer: A Multitask Explainable Learning Approach
Kianoosh Kazemi, Iman Azimi, Michelle Khine +3
Sleep is an essential component of human physiology, contributing significantly to overall health and quality of life. Accurate sleep staging and disorder detection are crucial for…
An LLM-Powered Agent for Physiological Data Analysis: A Case Study on PPG-based Heart Rate Estimation
Mohammad Feli, Iman Azimi, Pasi Liljeberg +1
Large language models (LLMs) are revolutionizing healthcare by improving diagnosis, patient care, and decision support through interactive communication. More recently, they have b…
Loneliness Forecasting Using Multi-modal Wearable and Mobile Sensing in Everyday Settings
Zhongqi Yang, Iman Azimi, Salar Jafarlou +7
The adverse effects of loneliness on both physical and mental well-being are profound. Although previous research has utilized mobile sensing techniques to detect mental health iss…
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…
Building Trust in Mental Health Chatbots: Safety Metrics and LLM-Based Evaluation Tools
Jung In Park, Mahyar Abbasian, Iman Azimi +11
Objective: This study aims to develop and validate an evaluation framework to ensure the safety and reliability of mental health chatbots, which are increasingly popular due to the…
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…
Integrating Wearable Sensor Data and Self-reported Diaries for Personalized Affect Forecasting
Zhongqi Yang, Yuning Wang, Ken S. Yamashita +6
Emotional states, as indicators of affect, are pivotal to overall health, making their accurate prediction before onset crucial. Current studies are primarily centered on immediate…
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…
Impact of Physical Activity on Quality of Life During Pregnancy: A Causal ML Approach
Kianoosh Kazemi, Iina Ryhtä, Iman Azimi +4
The concept of Quality of Life (QoL) refers to a holistic measurement of an individual's well-being, incorporating psychological and social aspects. Pregnant women, especially thos…
Differential Private Federated Transfer Learning for Mental Health Monitoring in Everyday Settings: A Case Study on Stress Detection
Ziyu Wang, Zhongqi Yang, Iman Azimi +1
Mental health conditions, prevalent across various demographics, necessitate efficient monitoring to mitigate their adverse impacts on life quality. The surge in data-driven method…
Robust CNN-based Respiration Rate Estimation for Smartwatch PPG and IMU
Kianoosh Kazemi, Iman Azimi, Pasi Liljeberg +1
Respiratory rate (RR) serves as an indicator of various medical conditions, such as cardiovascular diseases and sleep disorders. These RR estimation methods were mostly designed fo…
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.…