@article{2b30f90e95c1410b9f2299fd7201e74c,
title = "Accounting for age in prediction of discharge destination following elective lumbar fusion: a supervised machine learning approach",
keywords = "ACS-NSQIP, Age, Discharge disposition, Lumbar fusion, Machine learning, Predictive variables, Humans, Risk Factors, Patient Discharge, Infant, Insulins, Diabetes Mellitus, Type 1/complications, Postoperative Complications/epidemiology, Adult, Female, Spinal Fusion/adverse effects, Retrospective Studies, Supervised Machine Learning",
author = "Andrew Cabrera and Alexander Bouterse and Michael Nelson and Jacob Razzouk and Omar Ramos and Bono, \{Christopher M.\} and Wayne Cheng and Olumide Danisa",
note = "Copyright {\textcopyright} 2023 Elsevier Inc. All rights reserved.",
year = "2023",
month = jul,
doi = "10.1016/j.spinee.2023.03.015",
language = "English",
volume = "23",
pages = "997--1006",
journal = "Spine Journal",
issn = "1529-9430",
number = "7",
}