Quantifying intra-tumoral genetic heterogeneity of glioblastoma toward precision medicine using MRI and a data-inclusive machine learning algorithm.
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| Title: | Quantifying intra-tumoral genetic heterogeneity of glioblastoma toward precision medicine using MRI and a data-inclusive machine learning algorithm. |
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| Authors: | Wang L; H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America., Wang H; H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America., D'Angelo F; Institute for Cancer Genetics, Columbia University Medical Center, New York City, New York, United States of America., Curtin L; Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America., Sereduk CP; Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America., Leon G; Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America., Singleton KW; Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America., Urcuyo J; Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America., Hawkins-Daarud A; Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America., Jackson PR; Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America., Krishna C; Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America., Zimmerman RS; Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America., Patra DP; Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America., Bendok BR; Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America., Smith KA; Department of Neurosurgery, Barrow Neurological Institute-St. Joseph's Hospital and Medical Center, Phoenix, Arizona, United States of America., Nakaji P; Department of Neurosurgery, Barrow Neurological Institute-St. Joseph's Hospital and Medical Center, Phoenix, Arizona, United States of America., Donev K; Department of Pathology, Mayo Clinic Arizona, Phoenix, Arizona, United States of America., Baxter LC; Department of Neuropsychology, Mayo Clinic Arizona, Phoenix, Arizona, United States of America., Mrugała MM; Department of Neuro-Oncology, Mayo Clinic Arizona, Phoenix, Arizona, United States of America., Ceccarelli M; Department of Electrical Engineering and Information Technology, University of Naples 'Federico II', Naples, Italy., Iavarone A; Institute for Cancer Genetics, Columbia University Medical Center, New York City, New York, United States of America., Swanson KR; Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America., Tran NL; Department of Neurosurgery, Mayo Clinic Arizona, Phoenix, Arizona, United States of America.; Department of Cancer Biology, Mayo Clinic Arizona, Phoenix, Arizona, United States of America., Hu LS; Department of Radiology, Mayo Clinic Arizona, Phoenix, Arizona, United States of America., Li J; H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America. |
| Source: | PloS one [PLoS One] 2024 Apr 03; Vol. 19 (4), pp. e0299267. Date of Electronic Publication: 2024 Apr 03 (Print Publication: 2024). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1932-6203 |
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| DOI: | 10.1371/journal.pone.0299267 |
