Predicting post-surgical functional status in high-grade glioma with resting state fMRI and machine learning.
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| Title: | Predicting post-surgical functional status in high-grade glioma with resting state fMRI and machine learning. |
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| Authors: | Luckett PH; Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, USA. luckett.patrick@wustl.edu., Olufawo MO; Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, USA., Park KY; Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, USA., Lamichhane B; Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, USA.; Center for Health Sciences, Oklahoma State University, Tulsa, OK, USA., Dierker D; Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA., Verastegui GT; Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, USA., Lee JJ; Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA., Yang P; Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, USA., Kim A; Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, USA., Butt OH; Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA., Chheda MG; Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA., Snyder AZ; Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA.; Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA., Shimony JS; Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA., Leuthardt EC; Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, USA.; Department of Biomedical Engineering, Washington University in Saint Louis, St. Louis, MO, USA.; Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA.; Department of Mechanical Engineering and Materials Science, Washington University in Saint Louis, St. Louis, MO, USA.; Center for Innovation in Neuroscience and Technology, Washington University School of Medicine, St. Louis, MO, USA.; Brain Laser Center, Washington University School of Medicine, St. Louis, MO, USA.; National Center for Adaptive Neurotechnologies, Albany, NY, USA. |
| Source: | Journal of neuro-oncology [J Neurooncol] 2024 Aug; Vol. 169 (1), pp. 175-185. Date of Electronic Publication: 2024 May 24. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Springer Country of Publication: United States NLM ID: 8309335 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1573-7373 (Electronic) Linking ISSN: 0167594X NLM ISO Abbreviation: J Neurooncol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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