arXiv Machine Learning By Ziping Xu, Yuyi Chang, Chenshun Ni, Nithin Sugavanam, Asim H. Gazi, Pedja Klasnja, Emre Ertin, Susan A. Murphy

A Diffusion-Model Subpopulation Digital Twin for Mobile Health Deployment: A Case Study on the HeartSteps Intervention

Read the original on arXiv Machine Learning →

arXiv:2607. 21403v1 Announce Type: new Abstract: Mobile-health interventions increasingly use online learning and decision making algorithms to personalize when to nudge users toward healthier behavior, but a poorly designed algorithm can burden and disengage participants.

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arXiv AI
Jun 15

A Comparative Study of Deep Learning Architectures for Multi-Horizon Behavioural Forecasting for Mobile Health

arXiv:2606. 14604v1 Announce Type: cross Abstract: Wearable devices and smartphones generate rich behavioural time series that can support proactive health interventions, yet systematic comparisons of modern forecasting architectures for these data are lacking.

By Pavlos Nicolaou, Kleanthis Malialis, Artemis Kontou, Panayiotis Kolios
arXiv Machine Learning
Aug 20

Adaptive Multi-Agent Feature Selection for Personalized Fall Risk Prevention

The paper introduces PAFIR, a Personalized and Adaptive Feature selection framework that treats feature selection as a reinforcement learning problem over longitudinal multimodal health data. PAFIR jointly models structural dependencies among assessment variables and temporal dynamics in wearable-derived physical activity data, learning adaptive selection policies across repeated study visits using reward signals from sparse fall incidence outcomes. Applied to the Physio Feedback Exercise Program (PEER) trial, PAFIR outperforms state‑of‑the‑art baselines by capturing longitudinal and structural patterns of feature relevance, enabling dynamic, subject‑specific feature selection for more timely fall prevention strategies.

By Chang Liu, Ladda Thiamwong, Yanjie Fu, Rui Xie
arXiv AI
Aug 12

ComBodied Agents: a New Paradigm of Human-Centric Agentic AI

arXiv:2608. 10915v1 Announce Type: new Abstract: After an older adult misses a medication dose, a software agent can send another reminder and an embodied agent can bring the medication.

By Qianggang Ding, Xingyao Wang, Rui Feng, Zhibin Wang, Feixiang Wang, Kelong Mao, Hao Sun, Zhiyao Luo, Jiankai Tang, Lei Li, Jiadong Guo, Minheng Ni, Weicong Lin, Chenxi Yang, Hongxiang Gao, Zhenghua Chen, Yang Bai, Min Wu, Jun Cheng, Huazhu Fu, Dacheng Tao, Bang Liu