PT  - JOURNAL ARTICLE
AU  - Z. Shi
AU  - B. Hu
AU  - U.J. Schoepf
AU  - R.H. Savage
AU  - D.M. Dargis
AU  - C.W. Pan
AU  - X.L. Li
AU  - Q.Q. Ni
AU  - G.M. Lu
AU  - L.J. Zhang
TI  - Artificial Intelligence in the Management of Intracranial Aneurysms: Current Status and Future Perspectives
AID  - 10.3174/ajnr.A6468
DP  - 2020 Mar 12
TA  - American Journal of Neuroradiology
4099  - http://www.ajnr.org/content/early/2020/03/12/ajnr.A6468.short
4100  - http://www.ajnr.org/content/early/2020/03/12/ajnr.A6468.full
AB  - SUMMARY: Intracranial aneurysms with subarachnoid hemorrhage lead to high morbidity and mortality. It is of critical importance to detect aneurysms, identify risk factors of rupture, and predict treatment response of aneurysms to guide clinical interventions. Artificial intelligence has received worldwide attention for its impressive performance in image-based tasks. Artificial intelligence serves as an adjunct to physicians in a series of clinical settings, which substantially improves diagnostic accuracy while reducing physicians’ workload. Computer-assisted diagnosis systems of aneurysms based on MRA and CTA using deep learning have been evaluated, and excellent performances have been reported. Artificial intelligence has also been used in automated morphologic calculation, rupture risk stratification, and outcomes prediction with the implementation of machine learning methods, which have exhibited incremental value. This review summarizes current advances of artificial intelligence in the management of aneurysms, including detection and prediction. The challenges and future directions of clinical implementations of artificial intelligence are briefly discussed.AIartificial intelligenceAUCarea under the curveCADcomputer-assisted diagnosticsDLdeep learningFPfalse-positiveMLmachine learningSVMsupport vector machines