| Literature DB >> 33039000 |
Michael Tran Duong1, Andreas M Rauschecker2, Suyash Mohan3.
Abstract
Recent advances in artificial intelligence (AI) and deep learning (DL) hold promise to augment neuroimaging diagnosis for patients with brain tumors and stroke. Here, the authors review the diverse landscape of emerging neuroimaging applications of AI, including workflow optimization, lesion segmentation, and precision education. Given the many modalities used in diagnosing neurologic diseases, AI may be deployed to integrate across modalities (MR imaging, computed tomography, PET, electroencephalography, clinical and laboratory findings), facilitate crosstalk among specialists, and potentially improve diagnosis in patients with trauma, multiple sclerosis, epilepsy, and neurodegeneration. Together, there are myriad applications of AI for neuroradiology."Entities:
Keywords: Artificial intelligence; Deep learning; Epilepsy; Multiple sclerosis; Neural network; Neurodegeneration; Neuroradiology; Trauma
Year: 2020 PMID: 33039000 DOI: 10.1016/j.nic.2020.07.003
Source DB: PubMed Journal: Neuroimaging Clin N Am ISSN: 1052-5149 Impact factor: 2.264