A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models

E Christodoulou, J Ma, GS Collins… - Journal of clinical …, 2019 - Elsevier
Objectives The objective of this study was to compare performance of logistic regression
(LR) with machine learning (ML) for clinical prediction modeling in the literature. Study …

Artificial intelligence-driven prediction modeling and decision making in spine surgery using hybrid machine learning models

B Saravi, F Hassel, S Ülkümen, A Zink… - Journal of Personalized …, 2022 - mdpi.com
Healthcare systems worldwide generate vast amounts of data from many different sources.
Although of high complexity for a human being, it is essential to determine the patterns and …

The 5-item modified frailty index is predictive of severe adverse events in patients undergoing surgery for adult spinal deformity

M Yagi, T Michikawa, N Hosogane, N Fujita, E Okada… - Spine, 2019 - journals.lww.com
Study Design. A retrospective review of 281 consecutive cases of adult spine deformity
(ASD) surgery (age 55±19 yrs, 91% female, follow-up 4.3±1.9 yrs) from a multicenter …

Chronic preoperative opioid use is a risk factor for increased complications, resource use, and costs after cervical fusion

N Jain, JL Brock, FM Phillips, T Weaver, SN Khan - The Spine Journal, 2018 - Elsevier
Abstract Background Context As health-care transitions to value-based models, there has
been an increased focus on patient factors that can influence peri-and postoperative …

Predicting complication risk in spine surgery: a prospective analysis of a novel risk assessment tool

A Veeravagu, A Li, C Swinney, L Tian, A Moraff… - … of Neurosurgery: Spine, 2017 - thejns.org
OBJECTIVE The ability to assess the risk of adverse events based on known patient factors
and comorbidities would provide more effective preoperative risk stratification. Present risk …

Can machine learning algorithms accurately predict discharge to nonhome facility and early unplanned readmissions following spinal fusion? Analysis of a national …

A Goyal, C Ngufor, P Kerezoudis… - … of Neurosurgery: Spine, 2019 - thejns.org
OBJECTIVE Nonhome discharge and unplanned readmissions represent important cost
drivers following spinal fusion. The authors sought to utilize different machine learning …

[HTML][HTML] A machine learning approach for predictive models of adverse events following spine surgery

SS Han, TD Azad, PA Suarez, JK Ratliff - The Spine Journal, 2019 - Elsevier
BACKGROUND Rates of adverse events following spine surgery vary widely by patient-,
diagnosis-, and procedure-related factors. It is critical to understand the expected rates of …

Impact of frailty and comorbidities on surgical outcomes and complications in adult spinal disorders

M Yagi, N Fujita, E Okada, O Tsuji, N Nagoshi, T Tsuji… - Spine, 2018 - journals.lww.com
Study Design. Retrospective review of surgically treated 481 adult patients with spinal
disorders. Objective. The aim of this study was to elucidate the effect of frailty and …

Prediction models in degenerative spine surgery: a systematic review

D Lubelski, A Hersh, TD Azad… - Global spine …, 2021 - journals.sagepub.com
Study Design: Systematic review. Objectives: To review the existing literature of prediction
models in degenerative spinal surgery. Methods: Review of PubMed/Medline and Embase …

The path from big data analytics capabilities to value in hospitals: a sco** review

PY Brossard, E Minvielle, C Sicotte - BMC Health Services Research, 2022 - Springer
Background As the uptake of health information technologies increased, most healthcare
organizations have become producers of big data. A growing number of hospitals are …