Multi-output LSTM-based prediction of postoperative delirium: integrating baseline and perioperative data for enhanced risk stratification in older spine surgery patients

The proposed multi-output LSTM model predicted multiple clinical dimensions of postoperative delirium, highlighting baseline health status as a primary determinant. Strategic integration of comprehensive baseline assessments with acute perioperative data substantially enhances predictive accuracy, informing personalized delirium prevention and management strategies for improved perioperative outcomes in older spine surgery patients.

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Publication Details

Journal
BioData Mining
Published
2026-03-24
DOI
https://doi.org/10.1186/s13040-026-00531-7
Primary Topic
Intensive Care Unit Cognitive Disorders
Type
article
Field-Weighted Citation Impact
0.00
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article

Multi-output LSTM-based prediction of postoperative delirium: integrating baseline and perioperative data for enhanced risk stratification in older spine surgery patients

BioData Mining
Intensive Care Unit Cognitive Disorders
article

Multi-output LSTM-based prediction of postoperative delirium: integrating baseline and perioperative data for enhanced risk stratification in older spine surgery patients

article en

Abstract

The proposed multi-output LSTM model predicted multiple clinical dimensions of postoperative delirium, highlighting baseline health status as a primary determinant. Strategic integration of comprehensive baseline assessments with acute perioperative data substantially enhances predictive accuracy, informing personalized delirium prevention and management strategies for improved perioperative outcomes in older spine surgery patients.

BioData Mining
Yonsei University (KR), Yonsei University Health System (KR)
Zero hunger
Openalex Percentile: Top 13%
Intensive Care Unit Cognitive Disorders
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