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The performance of machine learning for predicting the recurrent stroke: a systematic review and meta-analysis on 24,350 patients.

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Title: The performance of machine learning for predicting the recurrent stroke: a systematic review and meta-analysis on 24,350 patients.
Authors: Habibi MA; Department of Neurosurgery, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran. mohammad.habibi1392@yahoo.com., Rashidi F; School of Medicine, Tehran University of Medical Sciences, Tehran, Iran., Mehrtabar E; Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Tehran University of Medical Sciences, Tehran, Iran., Arshadi MR; Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Tehran University of Medical Sciences, Tehran, Iran., Fallahi MS; Department of Neurosurgery, Tehran University of Medical Sciences, Tehran, Iran., Amirkhani N; School of Medicine, Tehran University of Medical Sciences, Tehran, Iran., Hajikarimloo B; Department of Neurological Surgery, University of Virginia, Charlottesville, USA., Shafizadeh M; Department of Neurosurgery, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran., Majidi S; Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, 10128, USA., Dmytriw AA; Neuroendovascular Program, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Source: Acta neurologica Belgica [Acta Neurol Belg] 2025 Jun; Vol. 125 (3), pp. 609-624. Date of Electronic Publication: 2024 Nov 07.
Publication Type: Journal Article; Systematic Review; Meta-Analysis
Journal Info: Publisher: Springer Country of Publication: Italy NLM ID: 0247035 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2240-2993 (Electronic) Linking ISSN: 03009009 NLM ISO Abbreviation: Acta Neurol Belg Subsets: MEDLINE
Database: MEDLINE Ultimate
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ISSN:2240-2993
DOI:10.1007/s13760-024-02682-y