Suzuki H, Aoki K, Chiba K et al (2015) Mutational landscape and clonal architecture in grade II and III gliomas. Nat Genet 47:458–468
Article CAS PubMed Google Scholar
Aoki K, Nakamura H, Suzuki H et al (2018) Prognostic relevance of genetic alterations in diffuse lower-grade gliomas. Neuro Oncol 20:66–77
Article CAS PubMed Google Scholar
Brat DJ, Verhaak RG, Aldape KD et al (2015) Comprehensive, integrative genomic analysis of diffuse lower-grade gliomas. N Engl J Med 372:2481–2498
Article CAS PubMed Google Scholar
Louis DN, Perry A, Wesseling P et al (2021) The 2021 WHO classification of tumors of the central nervous system: a summary. Neuro Oncol 23:1231–1251
Article CAS PubMed PubMed Central Google Scholar
Wijnenga MMJ, French PJ, Dubbink HJ et al (2018) The impact of surgery in molecularly defined low-grade glioma: an integrated clinical, radiological, and molecular analysis. Neuro Oncol 20:103–112
Article CAS PubMed Google Scholar
Ding X, Wang Z, Chen D et al (2018) The prognostic value of maximal surgical resection is attenuated in oligodendroglioma subgroups of adult diffuse glioma: a multicenter retrospective study. J Neurooncol 140:591–603
Fukuma R, Yanagisawa T, Kinoshita M et al (2019) Prediction of IDH and TERT promoter mutations in low-grade glioma from magnetic resonance images using a convolutional neural network. Sci Rep 9:20311
Article CAS PubMed PubMed Central Google Scholar
Chang K, Bai HX, Zhou H et al (2018) Residual convolutional neural network for the determination of IDH status in low- and high-grade gliomas from MR imaging. Clin Cancer Res 24:1073–1081
Article CAS PubMed Google Scholar
Chang P, Grinband J, Weinberg BD et al (2018) Deep-learning convolutional neural networks accurately classify genetic mutations in gliomas. AJNR Am J Neuroradiol 39:1201–1207
Article CAS PubMed PubMed Central Google Scholar
Matsui Y, Maruyama T, Nitta M et al (2020) Prediction of lower-grade glioma molecular subtypes using deep learning. J Neurooncol 146:321–327
Nalawade S, Murugesan GK, Vejdani-Jahromi M et al (2019) Classification of brain tumor isocitrate dehydrogenase status using MRI and deep learning. J Med Imaging (Bellingham) 6:046003
Choi YS, Bae S, Chang JH et al (2021) Fully automated hybrid approach to predict the IDH mutation status of gliomas via deep learning and radiomics. Neuro Oncol 23:304–313
Article CAS PubMed Google Scholar
van der Voort SR, Incekara F, Wijnenga MMJ et al (2022) Combined molecular subtyping, grading, and segmentation of glioma using multi-task deep learning. Neuro Oncol. https://doi.org/10.1093/neuonc/noac166
Article PubMed Central Google Scholar
Kim I, Choi HJ, Ryu JM et al (2019) A predictive model for high/low risk group according to oncotype DX recurrence score using machine learning. Eur J Surg Oncol 45:134–140
Twarish Alhamazani K, Alshudukhi J, Aljaloud S et al (2021) Implementation of machine learning models for the prevention of kidney diseases (CKD) or their derivatives. Comput Intell Neurosci 2021:3941978
Article PubMed PubMed Central Google Scholar
Choi S, Park J, Park S et al (2021) Establishment of a prediction tool for ocular trauma patients with machine learning algorithm. Int J Ophthalmol 14:1941–1949
Article PubMed PubMed Central Google Scholar
Lorenzo AJ, Rickard M, Braga LH et al (2019) Predictive analytics and modeling employing machine learning technology: the next step in data sharing, analysis, and individualized counseling explored with a large, prospective prenatal hydronephrosis database. Urology 123:204–209
Pawelka D, Laczmanska I, Karpinski P et al (2022) Machine-learning-based Analysis Identifies miRNA expression profile for diagnosis and prediction of colorectal cancer: a preliminary study. Cancer Genomics Proteomics 19:503–511
Article CAS PubMed PubMed Central Google Scholar
Park YJ, Bae JH, Shin MH et al (2019) Development of predictive models in patients with epiphora using lacrimal scintigraphy and machine learning. Nucl Med Mol Imaging 53:125–135
Article PubMed PubMed Central Google Scholar
Makino Y, Arakawa Y, Yoshioka E et al (2021) Prognostic stratification for IDH-wild-type lower-grade astrocytoma by Sanger sequencing and copy-number alteration analysis with MLPA. Sci Rep 11:14408
Article CAS PubMed PubMed Central Google Scholar
Jeuken J, Cornelissen S, Boots-Sprenger S et al (2006) Multiplex ligation-dependent probe amplification: a diagnostic tool for simultaneous identification of different genetic markers in glial tumors. J Mol Diagn 8:433–443
Article CAS PubMed PubMed Central Google Scholar
Kanda Y (2013) Investigation of the freely available easy-to-use software ‘EZR’ for medical statistics. Bone Marrow Transplant 48:452–458
Article CAS PubMed Google Scholar
Hrapsa I, Florian IA, Susman S et al (2022) External validation of a convolutional neural network for IDH mutation prediction. Medicina (Kaunas) 58:526
Xie Y, Zaccagna F, Rundo L et al (2022) Convolutional neural network techniques for brain tumor classification (from 2015 to 2022): review, challenges, and future perspectives. Diagnostics (Basel) 12:1850
Comments (0)