Clinical Artificial Intelligence Applications in Radiology: Neuro

Felipe Campos Kitamura; Ian Pan; Suely Fazio Ferraciolli; Kristen W Yeom; Nitamar Abdala

doi:10.1016/j.rcl.2021.07.002

Clinical Artificial Intelligence Applications in Radiology: Neuro

Radiol Clin North Am. 2021 Nov;59(6):1003-1012. doi: 10.1016/j.rcl.2021.07.002.

Authors

Felipe Campos Kitamura¹, Ian Pan², Suely Fazio Ferraciolli³, Kristen W Yeom⁴, Nitamar Abdala⁵

Affiliations

¹ DasaInova, Diagnósticos da América SA (Dasa), São Paulo, São Paulo, Brazil; Universidade Federal de São Paulo, São Paulo, São Paulo, Brazil. Electronic address: kitamura.felipe@gmail.com.
² DasaInova, Diagnósticos da América SA (Dasa), São Paulo, São Paulo, Brazil; Brigham and Woman's Hospital, Boston, MA, USA.
³ DasaInova, Diagnósticos da América SA (Dasa), São Paulo, São Paulo, Brazil.
⁴ Department of Radiology, Stanford University, CA, USA.
⁵ Universidade Federal de São Paulo, São Paulo, São Paulo, Brazil.

PMID: 34689869
DOI: 10.1016/j.rcl.2021.07.002

Abstract

Radiologists have been at the forefront of the digitization process in medicine. Artificial intelligence (AI) is a promising area of innovation, particularly in medical imaging. The number of applications of AI in neuroradiology has also grown. This article illustrates some of these applications. This article reviews machine learning challenges related to neuroradiology. The first approval of reimbursement for an AI algorithm by the Centers for Medicare and Medicaid Services, covering a stroke software for early detection of large vessel occlusion, is also discussed.

Keywords: Artificial intelligence; Clinical applications; Deep learning; Machine learning; Neuroradiology.

Publication types

Review

MeSH terms

Artificial Intelligence*
Brain / diagnostic imaging
Brain Diseases / diagnostic imaging*
Diagnostic Imaging / methods*
Humans
Image Interpretation, Computer-Assisted / methods*
Neuroimaging / methods*