Dynamic incremental learning with entropy-based task clustering and proxy gradients estimates blood glucose from PPG at 0.64 mmol/L MAE under subject-independent validation on a new 183-participant longitudinal benchmark.
Proceedings of the AAAI Conference on Artificial Intelligence , volume =
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Non-invasive Blood Glucose Estimation from Wearable Physiological Signals
Dynamic incremental learning with entropy-based task clustering and proxy gradients estimates blood glucose from PPG at 0.64 mmol/L MAE under subject-independent validation on a new 183-participant longitudinal benchmark.