9 papers
The Taxonomies, Training, and Applications of Event Stream Modelling for Electronic Health Records
Mingcheng Zhu, Yu Liu, Zhiyao Luo +1
The widespread adoption of electronic health records (EHRs) enables the acquisition of heterogeneous clinical data, spanning lab tests, vital signs, medications, and procedures, wh…
Standing on the Shoulders of Giants: Rethinking EEG Foundation Model Pretraining via Multi-Teacher Distillation
Chenqi Li, Yu Liu, Shuo Zhang +2
Pretraining for electroencephalogram (EEG) foundation models has predominantly relied on self-supervised masked reconstruction, a paradigm largely adapted from and inspired by the…
BioX-Bridge: Model Bridging for Unsupervised Cross-Modal Knowledge Transfer across Biosignals
Chenqi Li, Yu Liu, Timothy Denison +1
Biosignals offer valuable insights into the physiological states of the human body. Although biosignal modalities differ in functionality, signal fidelity, sensor comfort, and cost…
ProtoEHR: Hierarchical Prototype Learning for EHR-based Healthcare Predictions
Zi Cai, Yu Liu, Zhiyao Luo +1
Digital healthcare systems have enabled the collection of mass healthcare data in electronic healthcare records (EHRs), allowing artificial intelligence solutions for various healt…
Bridging Data Gaps of Rare Conditions in ICU: A Multi-Disease Adaptation Approach for Clinical Prediction
Mingcheng Zhu, Yu Liu, Zhiyao Luo +1
Artificial Intelligence has revolutionised critical care for common conditions. Yet, rare conditions in the intensive care unit (ICU), including recognised rare diseases and low-pr…
OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data
Jinwei Zeng, Yu Liu, Guozhen Zhang +4
Accurately estimating high-resolution carbon emissions is crucial for effective emission governance and mitigation planning. While conventional methods for precise carbon accountin…