참고문헌
- Takahashi K, Usuzaki T, Inamori R. Medical statistics unlock the gateway to further research: using deep learning to predict CDKN2A/B homozygous deletion in isocitrate dehydrogenase-mutant astrocytoma. Korean J Radiol 2023;24:1303-1305
- Park SH, Choi J, Byeon JS. Key principles of clinical validation, device approval, and insurance coverage decisions of artificial intelligence. Korean J Radiol 2021;22:442-453 https://doi.org/10.3348/kjr.2021.0048
- van der Ploeg T, Austin PC, Steyerberg EW. Modern modelling techniques are data hungry: a simulation study for predicting dichotomous endpoints. BMC Med Res Methodol 2014;14:137
- An C, Park YW, Ahn SS, Han K, Kim H, Lee SK. Radiomics machine learning study with a small sample size: single random training-test set split may lead to unreliable results. PLoS One 2021;16:e0256152
- Christodoulou E, Ma J, Collins GS, Steyerberg EW, Verbakel JY, Van Calster B. A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models. J Clin Epidemiol 2019;110:12-22 https://doi.org/10.1016/j.jclinepi.2019.02.004
- Park YW, Park KS, Park JE, Ahn SS, Park I, Kim HS, et al. Qualitative and quantitative magnetic resonance imaging phenotypes may predict CDKN2A/B homozygous deletion status in isocitrate dehydrogenase-mutant astrocytomas: a multicenter study. Korean J Radiol 2023;24:133-144 https://doi.org/10.3348/kjr.2022.0732
- Dosovitskiy A, Beyer L, Kolesnikov A, Weissenborn D, Zhai X, Unterthiner T, et al. An image is worth 16×16 words: transformers for image recognition at scale. arXiv:2010.11929 [Preprint]. [posted Oct 22, 2020; revised Jun 3, 2021; cited Sep 24, 2023]. https://arxiv.org/abs/2010.11929
- Hastie T, Tibshirani R, Friedman JH, Friedman JH. The elements of statistical learning: data mining, inference, and prediction. New York: Springer, 2009:347-369
- Lundberg SM, Lee SI. A unified approach to interpreting model predictions. In: Guyon I, Von Luxburg U, Bengio S, Wallach H, Fergus R, Vishwanathan S, et al., eds. 31th Annual Conference on Neural Information Processing Systems (NIPS 2017): Proceedings of the 30th International Conference on Neural Information Processing Systems; 2017 Dec 4-9; Long beach, United States of America. 2017:4768-4777
- Selvaraju RR, Cogswell M, Das A, Vedantam R, Parikh D, Batra D. Grad-cam: visual explanations from deep networks via gradient-based localization. Int J Comput Vis 2020;128:336-359 https://doi.org/10.1007/s11263-019-01228-7
- Lu VM, O'Connor KP, Shah AH, Eichberg DG, Luther EM, Komotar RJ, et al. The prognostic significance of CDKN2A homozygous deletion in IDH-mutant lower-grade glioma and glioblastoma: a systematic review of the contemporary literature. J Neurooncol 2020;148:221-229 https://doi.org/10.1007/s11060-020-03528-2
- Shirahata M, Ono T, Stichel D, Schrimpf D, Reuss DE, Sahm F, et al. Novel, improved grading system(s) for IDH-mutant astrocytic gliomas. Acta Neuropathol 2018;136:153-166 https://doi.org/10.1007/s00401-018-1849-4
- Appay R, Dehais C, Maurage CA, Alentorn A, Carpentier C, Colin C, et al. CDKN2A homozygous deletion is a strong adverse prognosis factor in diffuse malignant IDH-mutant gliomas. Neuro Oncol 2019;21:1519-1528 https://doi.org/10.1093/neuonc/noz124
- Gao J, Liu Z, Pan H, Cao X, Kan Y, Wen Z, et al. Preoperative discrimination of CDKN2A/B homozygous deletion status in isocitrate dehydrogenase-mutant astrocytoma: a deep learning-based radiomics model using MRI. J Magn Reson Imaging 2023 Aug 9. [Epub]. https://doi.org/10.1002/jmri.28945
- Zhang L, Wang R, Gao J, Tang Y, Xu X, Kan Y, et al. A novel MRI-based deep learning networks combined with attention mechanism for predicting CDKN2A/B homozygous deletion status in IDH-mutant astrocytoma. Eur Radiol 2023 Aug 8. [Epub]. https://doi.org/10.1007/s00330-023-09944-y