Electrocardiogram Report Generation and Question Answering via Retrieval-Augmented Self-Supervised Modeling

RespLLM: Unifying Audio and Text with Multimodal LLMs for Generalized Respiratory Health Prediction

FedEE: Uncertainty-Aware Personalized Federated Learning for Realistic Healthcare Applications

Towards open respiratory acoustic foundation models: Pretraining and benchmarking

Uncertainty-aware Health Diagnostics via Class-balanced Evidential Deep Learning

FLea: Addressing Data Scarcity and Label Skew in Federated Learning via Privacy-preserving Feature Augmentation

History-enhanced and Uncertainty-aware Trajectory Recovery via Attentive Neural Network

Healthy Cities: A comprehensive dataset for environmental determinants of health in England cities

Conditional Neural ODE Processes for Individual Disease Progression Forecasting: A Case Study on COVID-19

Cross-device Federated Learning for Mobile Health Diagnostics: A First Study on COVID-19 Detection

Exploring machine learning for audio-based respiratory condition screening: A concise review of databases, methods, and open issues

Precise mobility intervention for epidemic control using unobservable information via deep reinforcement learning

Exploring longitudinal cough, breath, and voice data for COVID-19 progression prediction via sequential deep learning: model development and validation

Smartphone app usage analysis: datasets, methods, and applications

Sounds of COVID-19: exploring realistic performance of audio-based digital testing

Quantifying the causal effect of individual mobility on health status in urban space

COVID-19 Sounds: A Large-Scale Audio Dataset for Digital Respiratory Screening

3dgcn: 3-dimensional dynamic graph convolutional network for citywide crowd flow prediction

Attnmove: History enhanced trajectory recovery via attentional network

DeepApp: Predicting personalized smartphone app usage via context-aware multi-task learning

Exploring automatic diagnosis of COVID-19 from crowdsourced respiratory sound data

Understanding Urban Dynamics via State-sharing Hidden Markov Model

Revealing Urban Dynamics by Learning Online and Offline Behaviours Together