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Article: Artificial Intelligence in Neuroradiology: A Review of Current Topics and Competition Challenges.

Wagner, Daniel T / Tilmans, Luke / Peng, Kevin / Niedermeier, Marilyn / Rohl, Matt / Ryan, Sean / Yadav, Divya / Takacs, Noah / Garcia-Fraley, Krystle / Koso, Mensur / Dikici, Engin / Prevedello, Luciano M / Nguyen, Xuan V

Diagnostics (Basel, Switzerland)

2023  Volume 13, Issue 16

Abstract: There is an expanding body of literature that describes the application of deep learning and other machine learning and artificial intelligence methods with potential relevance to neuroradiology practice. In this article, we performed a literature review ...

Abstract There is an expanding body of literature that describes the application of deep learning and other machine learning and artificial intelligence methods with potential relevance to neuroradiology practice. In this article, we performed a literature review to identify recent developments on the topics of artificial intelligence in neuroradiology, with particular emphasis on large datasets and large-scale algorithm assessments, such as those used in imaging AI competition challenges. Numerous applications relevant to ischemic stroke, intracranial hemorrhage, brain tumors, demyelinating disease, and neurodegenerative/neurocognitive disorders were discussed. The potential applications of these methods to spinal fractures, scoliosis grading, head and neck oncology, and vascular imaging were also reviewed. The AI applications examined perform a variety of tasks, including localization, segmentation, longitudinal monitoring, diagnostic classification, and prognostication. While research on this topic is ongoing, several applications have been cleared for clinical use and have the potential to augment the accuracy or efficiency of neuroradiologists.
Language English
Publishing date 2023-08-14
Publishing country Switzerland
Document type Journal Article ; Review
ZDB-ID 2662336-5
ISSN 2075-4418
ISSN 2075-4418
DOI 10.3390/diagnostics13162670
Database MEDical Literature Analysis and Retrieval System OnLINE

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