SynthesisNeurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology2026
Prediction and diagnosis of post-stroke epilepsy using artificial intelligence approaches: a systematic review and meta-analysis.
Synthesis in Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
introductionPost-stroke epilepsy (PSE) is a common complication following a stroke and is a major cause of epilepsy in the elderly. Artificial intelligence (AI) is currently developing rapidly in the medical field and has a promising outlook in disease diagnosis, treatment, and prognosis.
methodsWe screened five studies that fully met the requirements from the PubMed, Web of Science, and EMBASE databases using relevant search terms such as PSE and AI, and analyzed the role of AI in predicting and diagnosing PSE in these studies.
resultsThe results showed that the sensitivity of AI in predicting and diagnosing PSE was 88% (95% CI 0.78-0.94), and the specificity was 83% (95% CI 0.79-0.86). The area under the summary receiver operating characteristic (SROC) curve was 0.90 (95% CI 0.87-0.92).
conclusionThese results indicate that using AI to predict and assist in diagnosing PSE demonstrates high specificity and sensitivity, and has certain prospects in the future auxiliary diagnosis of PSE.
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