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American Journal of Neuroradiology
American Journal of Neuroradiology

American Journal of Neuroradiology

ASHNR American Society of Functional Neuroradiology ASHNR American Society of Pediatric Neuroradiology ASSR
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AJNR Awards, New Junior Editors, and more. Read the latest AJNR updates

MY CONTENT

  • ARTIFICIAL INTELLIGENCE
    You have access
    Integrating Clinical Data and Radiomics and Deep Learning Features for End-to-End Delayed Cerebral Ischemia Prediction on Noncontrast CT
    Qi-qi Ban, Hao-tian Zhang, Wei Wang, Yi-fan Du, Yi Zhao, Ai-jun Peng and Hang Qu
    American Journal of Neuroradiology July 2024, DOI: https://doi.org/10.3174/ajnr.A8301
  • Neurovascular/Stroke Imaging
    You have access
    A Comparison of CT Perfusion Output of RapidAI and Viz.ai Software in the Evaluation of Acute Ischemic Stroke
    Saif Bushnaq, Ameer E. Hassan, Adam Delora, Ali Kerro, Anita Datta, Rime Ezzeldin, Zuhair Ali, Tunmi Anwoju, Layla Nejad, Rene Silva, Yazan Diya Abualnadi, Zorain Mustafa Khalil and Mohamad Ezzeldin
    American Journal of Neuroradiology July 2024, 45 (7) 863-870; DOI: https://doi.org/10.3174/ajnr.A8196
  • ARTIFICIAL INTELLIGENCE
    You have access
    Assessing the Emergence and Evolution of Artificial Intelligence and Machine Learning Research in Neuroradiology
    Alexandre Boutet, Samuel S. Haile, Andrew Z. Yang, Hyo Jin Son, Mikail Malik, Vivek Pai, Mehran Nasralla, Jurgen Germann, Artur Vetkas, Farzad Khalvati and Birgit B. Ertl-Wagner
    American Journal of Neuroradiology June 2024, DOI: https://doi.org/10.3174/ajnr.A8252
  • ARTIFICIAL INTELLIGENCE
    You have access
    A Deep Learning Approach to Predict Recanalization First-Pass Effect following Mechanical Thrombectomy in Patients with Acute Ischemic Stroke
    Haoyue Zhang, Jennifer S. Polson, Zichen Wang, Kambiz Nael, Neal M. Rao, William F. Speier and Corey W. Arnold
    American Journal of Neuroradiology June 2024, DOI: https://doi.org/10.3174/ajnr.A8272
  • Artificial Intelligence
    You have access
    Evaluating Biases and Quality Issues in Intermodality Image Translation Studies for Neuroradiology: A Systematic Review
    Shannon L. Walston, Hiroyuki Tatekawa, Hirotaka Takita, Yukio Miki and Daiju Ueda
    American Journal of Neuroradiology June 2024, 45 (6) 826-832; DOI: https://doi.org/10.3174/ajnr.A8211
  • Pediatric Neuroimaging
    You have access
    Artificial Intelligence in the Future Landscape of Pediatric Neuroradiology: Opportunities and Challenges
    Aashim Bhatia, Farzad Khalvati and Birgit Betina Ertl-Wagner
    American Journal of Neuroradiology May 2024, 45 (5) 549-553; DOI: https://doi.org/10.3174/ajnr.A8086
  • ARTIFICIAL INTELLIGENCE
    You have access
    Evaluating Biases and Quality Issues in Intermodality Image Translation Studies for Neuroradiology: A Systematic Review
    Shannon L. Walston, Hiroyuki Tatekawa, Hirotaka Takita, Yukio Miki and Daiju Ueda
    American Journal of Neuroradiology April 2024, DOI: https://doi.org/10.3174/ajnr.A8211
  • Spine Imaging and Spine Image-Guided Interventions
    You have access
    Automated Detection of Cervical Spinal Stenosis and Cord Compression via Vision Transformer and Rules-Based Classification
    David L. Payne, Xuan Xu, Farshid Faraji, Kevin John, Katherine Ferra Pradas, Vahni Vishala Bernard, Lev Bangiyev and Prateek Prasanna
    American Journal of Neuroradiology April 2024, 45 (4) 432-438; DOI: https://doi.org/10.3174/ajnr.A8141
  • EDITOR'S CHOICENeurovascular/Stroke Imaging
    You have access
    A Clinical and Imaging Fused Deep Learning Model Matches Expert Clinician Prediction of 90-Day Stroke Outcomes
    Yongkai Liu, Preya Shah, Yannan Yu, Jai Horsey, Jiahong Ouyang, Bin Jiang, Guang Yang, Jeremy J. Heit, Margy E. McCullough-Hicks, Stephen M. Hugdal, Max Wintermark, Patrik Michel, David S. Liebeskind, Maarten G. Lansberg, Gregory W. Albers and Greg Zaharchuk
    American Journal of Neuroradiology April 2024, 45 (4) 406-411; DOI: https://doi.org/10.3174/ajnr.A8140

    The authors in this study used a deep learning-based predictive model (DLPD) that incorporated DWI and clinical data from the acute period to predict 90-day mRS outcomes and compared its predictions with those made by physicians. The results showed that the clinical and imaging fused deep learning model is noninferior to expert physicians in predicting specific mRS outcomes and unfavorable prognoses.

  • Artificial Intelligence
    You have access
    Identifying Patients with CSF-Venous Fistula Using Brain MRI: A Deep Learning Approach
    Shahriar Faghani, Mana Moassefi, Ajay A. Madhavan, Ian T. Mark, Jared T. Verdoorn, Bradley J. Erickson and John C. Benson
    American Journal of Neuroradiology April 2024, 45 (4) 439-443; DOI: https://doi.org/10.3174/ajnr.A8173

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