bioRxivBioinformaticsPreprint
Evaluating Long-Range Temporal Structure in Foundation Model-Based Forecasts of Heartbeat Dynamics
Abstract
We examine the long-range temporal structure of forecasts produced by Time-Series Foundation Models (TSFMs) on heartbeat dynamics using the MIT-BIH Normal Sinus Rhythm Database (NSRDB). Our findings indicate that these models do not adequately capture long-range dependencies, as reflected in growing errors in RR-interval predictions over longer forecast horizons. Code is available at https://github.com/SubramanianLab/ecg-tsfm-benchmark.
- organism: human
- assay: electronic health records
- research focus: benchmarking
- research focus: differential expression
- research focus: variant effect prediction
- research focus: drug response / drug discovery
- approach: deep learning
- approach: statistical model
- Citations
- 0
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