Future data points to implement in adult spinal deformity assessment for artificial intelligence modeling prediction: the importance of the biological dimension

S Haddad, J Pizones, R Raganato… - International Journal of …, 2023 - ijssurgery.com
Adult spinal deformity (ASD) surgery is still associated with high surgical risks. Machine
learning algorithms applied to multicenter databases have been created to predict outcomes …

[HTML][HTML] State-of-the-art reviews predictive modeling in adult spinal deformity: applications of advanced analytics

RS Joshi, D Lau, JK Scheer, M Serra-Burriel… - Spine deformity, 2021 - Springer
Adult spinal deformity (ASD) is a complex and heterogeneous disease that can severely
impact patients' lives. While it is clear that surgical correction can achieve significant …

[HTML][HTML] Artificial intelligence for adult spinal deformity

RS Joshi, AF Haddad, D Lau, CP Ames - Neurospine, 2019 - ncbi.nlm.nih.gov
Adult spinal deformity (ASD) is a complex disease that significantly affects the lives of many
patients. Surgical correction has proven to be effective in achieving improvement of …

Predicting surgical complications in patients undergoing elective adult spinal deformity procedures using machine learning

JS Kim, V Arvind, EK Oermann, D Kaji, W Ranson… - Spine deformity, 2018 - Elsevier
Abstract Study Design Cross-sectional database study. Objective To train and validate
machine learning models to identify risk factors for complications following surgery for adult …

[HTML][HTML] Predicting mechanical complications after adult spinal deformity operation using a machine learning based on modified global alignment and proportion …

SH Noh, HS Lee, GE Park, Y Ha, JY Park, SU Kuh… - Neurospine, 2023 - ncbi.nlm.nih.gov
Objective This study aimed to create an ideal machine learning model to predict mechanical
complications in adult spinal deformity (ASD) surgery based on GAPB (modified global …

Validation of adult spinal deformity surgical outcome prediction tools in adult symptomatic lumbar scoliosis

JP Wondra, MP Kelly, J Greenberg, EL Yanik, CP Ames… - Spine, 2023 - journals.lww.com
Study Design. A post hoc analysis. Objective. Advances in machine learning (ML) have led
to tools offering individualized outcome predictions for adult spinal deformity (ASD). Our …

Narrative review of predictive analytics of patient-reported outcomes in adult spinal deformity surgery

K Lehner, J Ehresman, Z Pennington… - Global Spine …, 2021 - journals.sagepub.com
Study Design: Narrative review Objective: Decision making in surgery for adult spinal
deformity (ASD) is complex due to the multifactorial etiology, numerous surgical options, 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 …

Validation of the ACS-NSQIP risk calculator: A machine-learning risk tool for predicting complications and mortality following adult spinal deformity corrective surgery

KE Pierce, BH Kapadia, S Naessig… - International journal of …, 2021 - ijssurgery.com
Objective To calculate the risk for postoperative complications and mortality after corrective
surgery of adult spinal deformity (ASD) patients using the American College of Surgeons …

Artificial intelligence models predict operative versus nonoperative management of patients with adult spinal deformity with 86% accuracy

WM Durand, AH Daniels, DK Hamilton, P Passias… - World neurosurgery, 2020 - Elsevier
Objective Patients with ASD show complex and highly variable disease. The decision to
manage patients operatively is largely subjective and varies based on surgeon training and …