Pharmacokinetic State Space Models for Unbiased Prediction of Haemodynamic Collapse

arXiv:2609.24338 · cs.LG · Submitted 2026-09-21 · Read on arXiv

cs.LG

Submitted: 2026-09-21

Updated: 2026-09-21

Comments: Published in Springer Nature after presenting at the International Conference on AI in Healthcare, London

DOI: 10.1007/978-3-032-35387-0_22

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Transformer — 19× in this paper · explained in 2 episodes
• Ablation — 7× in this paper · explained in 1 episode
• Hypotension Prediction Index — 7× in this paper
• Selection Bias — 4× in this paper · explained in 4 episodes
• Benchmark — 3× in this paper · explained in 2 episodes
• Fidelity — 3× in this paper · explained in 2 episodes
• Attention Mechanism — 2× in this paper · explained in 2 episodes
• External Validation — 2× in this paper · explained in 2 episodes
• Transformer Architecture — 2× in this paper · explained in 2 episodes
• AdamW Optimizer — 1× in this paper · explained in 1 episode
• Alert Fatigue — 1× in this paper · explained in 1 episode
• Area Under the Precision-Recall Curve — 1× in this paper
• Calibration — 1× in this paper · explained in 7 episodes
• Core — 1× in this paper · explained in 2 episodes
• Edge Devices — 1× in this paper · explained in 2 episodes
• Heart Rate — 1× in this paper
• Mean Arterial Pressure — 1× in this paper
• Positive Predictive Value — 1× in this paper
• Transformer Models — 1× in this paper · explained in 2 episodes

Sources

• Mamba: Linear-Time Sequence Modeling with Selective State Spaces
• Learning to Diagnose with LSTM Recurrent Neural Networks

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