Detection of Ruptures within UIA’s

Detection of Ruptures within UIA’s

Description

The AI tool in the study is designed to predict the likelihood of rupture in unruptured intracranial aneurysms (UIAs) by analyzing a combination of clinical, morphological, and hemodynamic data. Researchers found hemodynamic data to be especially important in predicting status of unruptured intercranial aneurysms. Researchers also determined logistic regression to be effective over machine learning algorithms for the parameters in this study.

Creator

Medical School of Nanjing University

Information

Pediatrics or Adult

Adult

Speciality

Neurology

Modality

CT

Training

807 patients (training), 200 patients (internal validation), and 108 patients (external validation)

Github

Publication

FDA

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