Physiology-based identifiable model-quantity subset selection for early prediction of intradialytic mean arterial pressure trajectories from sparse observations
A physiology-based model subset selection framework predicts intradialytic mean arterial pressure trajectories from sparse observations with 88.74% to 91.83% accuracy and 1.09 to 5.78 mmHg RMSE across four phenotypes.
Published Jul 17, 2026Paper ↗
67%
OverallHighly rated
?
OverallHighly ratedVote to see the score
Readers
–
Only vote on papers you've read. Sign in to vote.
AI panel3/20reviewers recommend it
lenient 1/5
medium 1/10
strict 1/5
AI panel?Vote to see what the 20 AI reviewers said
Abstract
andranges from 88.74% to 91.83% across the four phenotypes. Prediction-phase root-mean-square error ranges from 1.09 to 5.78 mmHg, and the maximum error ranges from 1.71 to 8.51 mmHg. This patient-type-level framework enables interpretable MAP trajectory prediction and provides a methodological basis for future patient-level evaluation of IDH-related MAP decline.