115 citations · 183 across the 18 of their papers we have counts for
6 papers · 1 filter
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…
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…
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…
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…