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For: Zhou H, Hu R, Tang O, Hu C, Tang L, Chang K, Shen Q, Wu J, Zou B, Xiao B, Boxerman J, Chen W, Huang RY, Yang L, Bai HX, Zhu C. Automatic Machine Learning to Differentiate Pediatric Posterior Fossa Tumors on Routine MR Imaging. AJNR Am J Neuroradiol 2020;41:1279-85. [PMID: 32661052 DOI: 10.3174/ajnr.A6621] [Cited by in Crossref: 24] [Cited by in F6Publishing: 25] [Article Influence: 12.0] [Reference Citation Analysis]
Number Citing Articles
1 Yearley AG, Blitz SE, Patel RV, Chan A, Baird LC, Friedman GK, Arnaout O, Smith TR, Bernstock JD. Machine Learning in the Classification of Pediatric Posterior Fossa Tumors: A Systematic Review. Cancers 2022;14:5608. [DOI: 10.3390/cancers14225608] [Reference Citation Analysis]
2 Zhang N, Zhang D, Sun J, Sun H, Ge M. Contribution of tumor characteristics and surgery-related factors to symptomatic hydrocephalus after posterior fossa tumor resection: a single-institution experience. Journal of Neurosurgery: Pediatrics 2022. [DOI: 10.3171/2022.10.peds22281] [Reference Citation Analysis]
3 Alsubai S, Khan HU, Alqahtani A, Sha M, Abbas S, Mohammad UG. Ensemble deep learning for brain tumor detection. Front Comput Neurosci 2022;16:1005617. [DOI: 10.3389/fncom.2022.1005617] [Reference Citation Analysis]
4 Brancato V, Cerrone M, Lavitrano M, Salvatore M, Cavaliere C. A Systematic Review of the Current Status and Quality of Radiomics for Glioma Differential Diagnosis. Cancers (Basel) 2022;14:2731. [PMID: 35681711 DOI: 10.3390/cancers14112731] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
5 Zhang M, Tam L, Wright J, Mohammadzadeh M, Han M, Chen E, Wagner M, Nemalka J, Lai H, Eghbal A, Ho CY, Lober RM, Cheshier SH, Vitanza NA, Grant GA, Prolo LM, Yeom KW, Jaju A. Radiomics Can Distinguish Pediatric Supratentorial Embryonal Tumors, High-Grade Gliomas, and Ependymomas. AJNR Am J Neuroradiol 2022. [PMID: 35361575 DOI: 10.3174/ajnr.A7481] [Reference Citation Analysis]
6 Singh NM, Harrod JB, Subramanian S, Robinson M, Chang K, Cetin-Karayumak S, Dalca AV, Eickhoff S, Fox M, Franke L, Golland P, Haehn D, Iglesias JE, O'Donnell LJ, Ou Y, Rathi Y, Siddiqi SH, Sun H, Westover MB, Whitfield-Gabrieli S, Gollub RL. How Machine Learning is Powering Neuroimaging to Improve Brain Health. Neuroinformatics 2022. [PMID: 35347570 DOI: 10.1007/s12021-022-09572-9] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
7 Kalasauskas D, Kosterhon M, Keric N, Korczynski O, Kronfeld A, Ringel F, Othman A, Brockmann MA. Beyond Glioma: The Utility of Radiomic Analysis for Non-Glial Intracranial Tumors. Cancers (Basel) 2022;14:836. [PMID: 35159103 DOI: 10.3390/cancers14030836] [Reference Citation Analysis]
8 Kurokawa R, Umemura Y, Capizzano A, Kurokawa M, Baba A, Holmes A, Kim J, Ota Y, Srinivasan A, Moritani T. Dynamic susceptibility contrast and diffusion-weighted MRI in posterior fossa pilocytic astrocytoma and medulloblastoma. J Neuroimaging 2022. [PMID: 34997668 DOI: 10.1111/jon.12962] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
9 Ina Ly K, Gerstner ER. Imaging of CNS ependymomas. Handbook of Neuro-Oncology Neuroimaging 2022. [DOI: 10.1016/b978-0-12-822835-7.00033-0] [Reference Citation Analysis]
10 Ramesh S, Chokkara S, Shen T, Major A, Volchenboum SL, Mayampurath A, Applebaum MA. Applications of Artificial Intelligence in Pediatric Oncology: A Systematic Review. JCO Clin Cancer Inform 2021;5:1208-19. [PMID: 34910588 DOI: 10.1200/CCI.21.00102] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
11 Krauze AV, Camphausen K. Molecular Biology in Treatment Decision Processes-Neuro-Oncology Edition. Int J Mol Sci 2021;22:13278. [PMID: 34948075 DOI: 10.3390/ijms222413278] [Reference Citation Analysis]
12 Dong J, Li S, Li L, Liang S, Zhang B, Meng Y, Zhang X, Zhang Y, Zhao S. Differentiation of paediatric posterior fossa tumours by the multiregional and multiparametric MRI radiomics approach: a study on the selection of optimal multiple sequences and multiregions. Br J Radiol 2021;:20201302. [PMID: 34767476 DOI: 10.1259/bjr.20201302] [Reference Citation Analysis]
13 Abdel Razek AAK, Alksas A, Shehata M, AbdelKhalek A, Abdel Baky K, El-Baz A, Helmy E. Clinical applications of artificial intelligence and radiomics in neuro-oncology imaging. Insights Imaging 2021;12:152. [PMID: 34676470 DOI: 10.1186/s13244-021-01102-6] [Cited by in Crossref: 8] [Cited by in F6Publishing: 9] [Article Influence: 8.0] [Reference Citation Analysis]
14 Ak M, Toll SA, Hein KZ, Colen RR, Khatua S. Evolving Role and Translation of Radiomics and Radiogenomics in Adult and Pediatric Neuro-Oncology. AJNR Am J Neuroradiol 2021. [PMID: 34649914 DOI: 10.3174/ajnr.A7297] [Cited by in Crossref: 3] [Cited by in F6Publishing: 5] [Article Influence: 3.0] [Reference Citation Analysis]
15 Huang J, Shlobin NA, Lam SK, DeCuypere M. Artificial Intelligence Applications in Pediatric Brain Tumor Imaging: A Systematic Review. World Neurosurg 2021;157:99-105. [PMID: 34648981 DOI: 10.1016/j.wneu.2021.10.068] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
16 Ge G, Liu F, Zhang G. Optimization of running-in surface morphology parameters based on the AutoML model. PLoS One 2021;16:e0257850. [PMID: 34606518 DOI: 10.1371/journal.pone.0257850] [Reference Citation Analysis]
17 Zhang M, Wong SW, Lummus S, Han M, Radmanesh A, Ahmadian SS, Prolo LM, Lai H, Eghbal A, Oztekin O, Cheshier SH, Fisher PG, Ho CY, Vogel H, Vitanza NA, Lober RM, Grant GA, Jaju A, Yeom KW. Radiomic Phenotypes Distinguish Atypical Teratoid/Rhabdoid Tumors from Medulloblastoma. AJNR Am J Neuroradiol 2021;42:1702-8. [PMID: 34266866 DOI: 10.3174/ajnr.A7200] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 5.0] [Reference Citation Analysis]
18 Sulman EP, Eisenstat DD. World Cancer Day 2021 - Perspectives in Pediatric and Adult Neuro-Oncology. Front Oncol 2021;11:659800. [PMID: 34041027 DOI: 10.3389/fonc.2021.659800] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
19 Artzi M, Redmard E, Tzemach O, Zeltser J, Gropper O, Roth J, Shofty B, Kozyrev DA, Constantini S, Ben-sira L. Classification of Pediatric Posterior Fossa Tumors Using Convolutional Neural Network and Tabular Data. IEEE Access 2021;9:91966-73. [DOI: 10.1109/access.2021.3085771] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
20 Khan P, Kader MF, Islam SMR, Rahman AB, Kamal MS, Toha MU, Kwak K. Machine Learning and Deep Learning Approaches for Brain Disease Diagnosis: Principles and Recent Advances. IEEE Access 2021;9:37622-55. [DOI: 10.1109/access.2021.3062484] [Cited by in Crossref: 18] [Cited by in F6Publishing: 20] [Article Influence: 18.0] [Reference Citation Analysis]