Die Wirbelsäule, Table of Contents Die Wirbelsäule 2025; 09(03): 122-123DOI: 10.1055/a-2542-6969 Referiert und kommentiert Kommentar zu: Lumbale Bandscheibenchirurgie: Maschinenlernen sagt Operationserfolg voraus Authors Dominik Laue Lennard M. Wurm Recommend Article Abstract Buy Article(opens in new window) Comment on:Lumbale Bandscheibenchirurgie: Maschinenlernen sagt Operationserfolg vorausDie Wirbelsäule 2025; 09(03): 121-122DOI: 10.1055/a-2542-6937 Full Text References Literatur 1 Staartjes VE, Schröder ML. Deep learning-based preoperative predictive analytics for patient-reported outcomes following lumbar discectomy: feasibility of center-specific modeling. J Neurosurg Spine 2019; 31: 568-574 2 Halicka M, Minarikova D, Theis JC. et al. Predicting patient-reported outcomes following lumbar spine surgery: development and external validation of multivariable prediction models. BMC Musculoskelet Disord 2023; 24: 173 3 Ghanem A, Labrom RD, Walter CM. et al. Limitations in evaluating machine learning models for imbalanced binary outcome classification in spine surgery: a systematic review. Brain Sci 2023; 13: 1723 4 Wirries N, Herlyn P, Schmieder K. et al. Implications of preoperative depression for lumbar spine surgery outcomes. JAMA Netw Open 2022; 5: e2251821 5 Wurm LM, Fischer B, Neuschmelting V. et al. Rapid, label-free classification of glioblastoma differentiation status combining confocal Raman spectroscopy and machine learning. Analyst 2023; 148: 6109-6119