3 citations · 5 across the 6 of their papers we have counts for
6 papers
TimeSRL: Generalizable Time-Series Behavioral Modeling via Semantic RL-Tuned LLMs -- A Case Study in Mental Health
Yuang Fan, Lilin Xu, Millie Wu +8
Longitudinal passive sensing enables continuous health prediction, yet models often fail under cross-dataset distribution shifts. Traditional ML overfits cohort-specific artifacts,…
Distributional Decomposition of Consumption Inequality Change During COVID-19
Utkarsh Anand, Xin Liu
We decompose the U.S. consumption inequality distributional changes during the COVID-19 phase. Analyzing the Consumption Expenditure Interview Survey data, we decompose observed ch…
Towards a General Intelligence and Interface for Wearable Health Data
Girish Narayanswamy, Maxwell A. Xu, A. Ali Heydari +37
While ubiquitous wearable sensors capture a wealth of behavioral and physiological information, effectively transforming these signals into personalized health insights is challeng…
Insulin Resistance Prediction From Wearables and Routine Blood Biomarkers
Ahmed A. Metwally, A. Ali Heydari, Daniel McDuff +9
Insulin resistance, a precursor to type 2 diabetes, is characterized by impaired insulin action in tissues. Current methods for measuring insulin resistance, while effective, are e…
Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium
Hyewon Jeong, Sarah Jabbour, Yuzhe Yang +40
The third ML4H symposium was held in person on December 10, 2023, in New Orleans, Louisiana, USA. The symposium included research roundtable sessions to foster discussions between…
Demographic Bias of Expert-Level Vision-Language Foundation Models in Medical Imaging
Yuzhe Yang, Yujia Liu, Xin Liu +6
Advances in artificial intelligence (AI) have achieved expert-level performance in medical imaging applications. Notably, self-supervised vision-language foundation models can dete…