Machine learning in the diagnosis and prognosis of transient ischaemic attack: a systematic review

Abstract Background Transient ischaemic attack (TIA) is a major risk factor for stroke, with up to 15% of patients experiencing an event within 90 days, a large proportion in the first 48 h. Accurate diagnosis and prognostic stratification remain challenging due to transient symptoms, lack of biomar...

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Auteurs principaux:	Kishan Desor, Ahmed Elmewafy, Eyad Jamileh, Aref Jalal Eldin, Ibrahim Antoun
Format:	Artigo
Langue:	Inglês
Publié:	BMC 2026-03-01
Collection:	BMC Neurology
Sujets:	Machine learning Artificial intelligence Transient ischaemic attack Cerebrovascular event Stroke
Accès en ligne:	https://doi.org/10.1186/s12883-026-04834-4
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