The performance of artificial intelligence in image-based prediction of hematoma enlargement: a systematic review and meta-analysis

Abstract

BACKGROUND: Accurately predicting hematoma enlargement (HE) is crucial for improving the prognosis of patients with cerebral haemorrhage. Artificial intelligence (AI) is a potentially reliable assistant for medical image recognition. This study systematically reviews medical imaging articles on the predictive performance of AI in HE. MATERIALS AND METHODS: Retrieved relevant studies published before October, 2024 from Embase, Institute of Electrical and Electronics Engineers (IEEE), PubMed, Web of Science, and Cochrane Library databases. The diagnostic test of predicting hematoma enlargement based on CT image training artificial intelligence model, and reported 2 × 2 contingency tables or provided sensitivity (SE) and specificity (SP) for calculation. Two reviewers independently screened the retrieved citations and extracted data. The methodological quality of studies was assessed using the QUADAS-AI, and Preferred Reporting Items for Systematic reviews and Meta-Analyses was used to ensure standardised reporting of studies. Subgroup analysis was performed based on sample size, risk of bias, year of publication, ratio of training set to test set, and number of centres involved. RESULTS: < 0.001. CONCLUSIONS: Artificial intelligence algorithms based on imaging have shown good performance in predicting HE.

Ähnliche Arbeiten