Page 18 - AIH-2-4
P. 18

Artificial Intelligence in Health                                              AI in acute stroke imaging



               CT imaging. Sci Program. 2021;2021:1-10.           Ethical challenges and evolving strategies in the integration
                                                                  of  artificial  intelligence  into  clinical  practice.  PLOS Digit
               doi: 10.1155/2021/3554718
                                                                  Health. 2025;4(4):e0000810.
            68.  Shlobin NA, Baig AA, Waqas M, et al. Artificial intelligence      doi: 10.1371/journal.pdig.0000810
               for large-vessel occlusion stroke: A systematic review. World
               Neurosurg. 2022;159:207-220.e1.                 74.  Siala H, Wang Y. SHIFTing artificial intelligence to be
                                                                  responsible in healthcare: A systematic review. Soc Sci Med.
               doi: 10.1016/j.wneu.2021.12.004
                                                                  2022;296:114782.
            69.  Zebrowitz E, Dadoo S, Brabant P, et al. The impact of artificial      doi: 10.1016/j.socscimed.2022.114782
               intelligence on large vessel occlusion stroke detection and
               management: A  systematic review meta-analysis.  Intell   75.  Kelly CJ, Karthikesalingam A, Suleyman M, Corrado G,
               Based Med. 2024;10:100161.                         King D. Key challenges for delivering clinical impact with
                                                                  artificial intelligence. BMC Med. 2019;17(1):195.
               doi: 10.1016/j.ibmed.2024.100161
                                                                  doi: 10.1186/s12916-019-1426-2
            70.  Murray NM, Unberath M, Hager GD, Hui FK. Artificial
               intelligence to diagnose ischemic stroke and identify large   76.  Marey A, Arjmand P, Alerab ADS,  et al. Explainability,
               vessel occlusions: A  systematic review.  J  NeuroIntervent   transparency and black box challenges of AI in radiology:
               Surg. 2020;12(2):156-164.                          Impact on patient care in cardiovascular radiology. Egypt J
                                                                  Radiol Nucl Med. 2024;55(1):183.
               doi: 10.1136/neurintsurg-2019-015135
                                                                  doi: 10.1186/s43055-024-01356-2
            71.  Dantas J, Ribeiro G, Dagostin C,  et al. Can artificial
               intelligence to detect large vessel occlusion improve patient   77.  Neri E, Aghakhanyan G, Zerunian M, et al. Explainable AI in
               care? A systematic review and meta-analysis (P5-5.026).   radiology: A white paper of the Italian Society of Medical and
               Neurology. 2024;102(17_supplement_1):6072.         Interventional Radiology. Radiol Med. 2023;128(6):755-764.
                                                                  doi: 10.1007/s11547-023-01634-5
               doi: 10.1212/WNL.0000000000206218
                                                               78.  Shurrab S, Guerra-Manzanares A, Magid A, Piechowski-
            72.  Leveraging teleradiology with artificial intelligence.  Bull   Jozwiak B, Atashzar SF, Shamout FE. Multimodal machine
               World Health Organ. 2025;103(2):86-87.
                                                                  learning for stroke prognosis and diagnosis: A  systematic
               doi: 10.2471/BLT.25.020225                         review. IEEE J Biomed Health Inform. 2024;28(11):6958-6973.
            73.  Weiner EB, Dankwa-Mullan I, Nelson WA, Hassanpour S.      doi: 10.1109/JBHI.2024.3448238






































            Volume 2 Issue 4 (2025)                         12                          doi: 10.36922/AIH025140025
   13   14   15   16   17   18   19   20   21   22   23