Newswise — Rolling Meadows, IL (June 1, 2023). The June issue is Neurosurgery focus (Volume 54, No. 6) [https://thejns.org/focus/view/journals/neurosurg-focus/54/6/neurosurg-focus.54.issue-6.xml]) presents 16 articles on the increasing use of machine learning in neurosurgical research and practice.
Topic editor: Mohammad Baidon, John H. Singh, Shelley D. Timmons, Eric A. Potts
The June issue is Neurosurgery focus focuses on new developments leading to increased use of machine learning in neurosurgery. In this issue, “the authors study current machine learning models, evaluate new algorithms, and discuss approaches to evaluating machine learning techniques in neurosurgery,” the topic editor notes, adding that this “We hope that the issue will contribute to the provision of long-term care.” It is informative for clinicians and scientists, stimulates scientific thinking, and provides a framework for fruitful conversations on highly complex and challenging subjects. ”
Contents of the June issue:
- “Introduction. Machine Learning in Neurosurgery: Transitioning Modern Medicine into a New Era” By Mohammad Baidon et al.
- “Quantification of movement during microvascular anastomosis simulation using hand detection by machine learning” Nicolas I. Gonzalez-Romo et al.
- “Critical Reading of the Machine Learning Literature in Neurosurgery: A Reader’s Guide and Checklist for Evaluating Predictive Models” By Shivaram Emani et al.
- “Metabolomic differentiation of tumor center and edge in glioma” Mary E. Baxter and others
- “Which supervised machine learning algorithm best predicts the attainment of minimal clinically important differences in postoperative neck pain in patients with cervical myelopathy? A QOD study” by Christine Park et al.
- “Interhemispheric connectivity in language proficiency maintenance and prognosis prediction: fully connected layer-based deep learning model analysis” By Haosu Zhang et al.
- “Development of a nonlinear k-nearest neighbor classification algorithm to identify patients at high risk of long hospital stay after spine surgery” Written by Shane Shahrestani et al.
- “Machine Learning Predictive Models in Neurosurgery: Evaluation Based on TRIPOD Guidelines. A Systematic Review” by Anmol Warman et al.
- “Incorporating biparietal constriction metrics to improve the ability of machine learning models to detect sagittal craniosynostosis in 2D photographs” By Megan G. Anderson et al.
- “Surgical Classification Using Natural Language Processing of Informed Consent Forms in Spine Surgery” Michael D. Shost et al.
- “Detection of MRI-based cervical ossification of the posterior longitudinal ligament using a new automated machine learning diagnostic tool” By Shachar Shemesh et al.
- “Using machine learning to predict 30-day readmission and reoperation after supratentorial high-grade glioma resection: the ACS NSQIP study of 9,418 patients” Written by Abdul Karim Gais and others.
- “Evaluation of 3D Deep Learning Pipeline for Cerebrovascular and Intracranial Aneurysm Segmentation from Computed Tomography Angiography and Digital Subtraction Angiography Image Pairs” Tatsat R. Patel et al.
- “Comparison of Machine Learning Models for Predicting Long-Term Outcomes After Severe Traumatic Brain Injury” Dooman Arefan and others
- “Immunohistochemical markers predicting long-term recurrence after cervical spine and chordoma resection: a multicenter study” Written by Abdul Karim Gais and others.
- “Machine Learning for Automating 2-D to 3-D Automatic Registration of the Spine in Real-Time Using a Single Radiograph” Written by Andrew Abu Musa et al.
- “Radioactive Signature of Meningioma Using Ki-67 Proliferative Index as a Prognostic Marker of Clinical Outcome” Omaditya Khanna et al.
Please read this month’s issue. Neurosurgery focus.
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Article bans and author/expert interviews: Please contact Gillian Shasby, JNSPG Publishing Director. [email protected] Arrange interviews with the authors and external experts who can be accessed in advance and provide background to this study.
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World leader in cutting-edge neurosurgical research since 1944 Journal of Neurosurgery (www.thejns.org) is the official journal of the American Society of Neurological Surgeons (AANS), representing more than 12,000 members worldwide (www.AANS.org).
