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Application of artificial intelligence in brain arteriovenous malformations: Angioarchitectures, clinical symptoms and prognosis prediction.
Li, Xiangyu; Xiang, Sishi; Li, Guilin.
Afiliación
  • Li X; Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China.
  • Xiang S; Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China.
  • Li G; Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China.
Interv Neuroradiol ; : 15910199241238798, 2024 Mar 22.
Article en En | MEDLINE | ID: mdl-38515371
ABSTRACT

BACKGROUND:

Artificial intelligence (AI) has rapidly advanced in the medical field, leveraging its intelligence and automation for the management of various diseases. Brain arteriovenous malformations (AVM) are particularly noteworthy, experiencing rapid development in recent years and yielding remarkable results. This paper aims to summarize the applications of AI in the management of AVMs management.

METHODS:

Literatures published in PubMed during 1999-2022, discussing AI application in AVMs management were reviewed.

RESULTS:

AI algorithms have been applied in various aspects of AVM management, particularly in machine learning and deep learning models. Automatic lesion segmentation or delineation is a promising application that can be further developed and verified. Prognosis prediction using machine learning algorithms with radiomic-based analysis is another meaningful application.

CONCLUSIONS:

AI has been widely used in AVMs management. This article summarizes the current research progress, limitations and future research directions.
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Interv Neuroradiol Asunto de la revista: NEUROLOGIA / RADIOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Interv Neuroradiol Asunto de la revista: NEUROLOGIA / RADIOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: China