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Predicting arterial pressure without prejudice: towards effective hypotension prediction models
Simon Tilma Vistisen1, Paul Elbers2
1Department of Clinical Medicine, Aarhus University, Aarhus, Denmark; Department of Anesthesiology and Intensive Care, Aarhus University Hospital, Aarhus, Denmark.
Selection bias in hypotension prediction models distorts algorithm learning. Unbiased data enables models to learn more from arterial waveforms beyond current blood pressure, improving accuracy.
Area of Science:
- Medical informatics
- Machine learning in healthcare
- Physiological signal processing
Background:
- Selection bias is a known issue in hypotension prediction models.
- The specific impact of this bias on model learning from arterial waveforms is not well understood.
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