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Machine learning-based prediction of proximal junctional pathology after adult spinal deformity surgery: a systematic review and diagnostic test accuracy meta-analysis.

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Bibliographic Details
Title: Machine learning-based prediction of proximal junctional pathology after adult spinal deformity surgery: a systematic review and diagnostic test accuracy meta-analysis.
Authors: Patel S; Department of Neurological Surgery, Thomas Jefferson University Hospital, Philadelphia, PA, USA., Nischal SA; Department of Physiology, Anatomy & Genetics, Medical Sciences Division, University of Oxford, Oxford, UK. shiva.nischal@dpag.ox.ac.uk., Chai YH; University College London Medical School, University College London, London, UK., Kale KM; Department of Physiology, Anatomy & Genetics, Medical Sciences Division, University of Oxford, Oxford, UK., Hines K; Department of Neurological Surgery, Thomas Jefferson University Hospital, Philadelphia, PA, USA., Heller J; Department of Neurological Surgery, Thomas Jefferson University Hospital, Philadelphia, PA, USA., Jallo J; Department of Neurological Surgery, Thomas Jefferson University Hospital, Philadelphia, PA, USA., Harrop JS; Department of Neurological Surgery, Thomas Jefferson University Hospital, Philadelphia, PA, USA., Prasad SK; Department of Neurological Surgery, Thomas Jefferson University Hospital, Philadelphia, PA, USA.
Source: Acta neurochirurgica [Acta Neurochir (Wien)] 2026 May 07; Vol. 168 (1). Date of Electronic Publication: 2026 May 07.
Publication Type: Journal Article; Systematic Review; Meta-Analysis; Review
Journal Info: Publisher: Springer Country of Publication: Austria NLM ID: 0151000 Publication Model: Electronic Cited Medium: Internet ISSN: 0942-0940 (Electronic) Linking ISSN: 00016268 NLM ISO Abbreviation: Acta Neurochir (Wien) Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:0942-0940
DOI:10.1007/s00701-026-06876-6