Papers for

pediatric sleep clinicians

Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.

Global time aware conditioning improves pediatric sleep data analysis

Global Time-Aware Conditioning (GTC): A Mechanism for Time-Aware Pediatric Sleep Representation Learning

Abstract: Sleep physiology evolves throughout the night, with changes in sleep cycles, respiratory stability, and cardiovascular dynamics. However, self-supervised learning (SSL) methods for sleep typically process short, fixed-duration windows without explicitly modeling where each window occurs within the full sleep session. We introduce Global Time-Aware Conditioning (GTC), a mechanism that complements local positional encodings by conditioning latent representations on the global time-of-sleep of each input window. We integrate GTC into three representative SSL frameworks and evaluate them on five clinically relevant tasks with extreme class imbalance across two independent pediatric cohorts. GTC generally improves F1 and AUPRC across architectures and tasks, with gains persisting under cross-cohort transfer, highlighting the value of global temporal context for sleep representation learning.

Mon 19 OctMachine Learning

The gist

Sleep changes throughout the night, but current computer methods usually look only at short parts of sleep without considering when those parts happen. The paper introduces a new way called Global Time-Aware Conditioning (GTC) that includes information about the exact time during sleep in the analysis. The authors added GTC to several existing methods and tested it on different tasks involving children's sleep data. They found that GTC helped the methods work better, especially when using data from different groups of children.

Open → 2610.26618v1