Uncertainty-aware deep learning for trustworthy prediction of long-term outcome after endovascular thrombectomy … – Nature.com
Global Burden of Disease Stroke Expert Group and others. Global, regional, and country-specific lifetime risks of stroke, 1990 and 2016. N. Engl. J. Med. 379, 24292437 (2018).
Article Google Scholar
Goyal, M. et al. Endovascular thrombectomy after large-vessel Ischaemic stroke: A meta-analysis of individual patient data from five randomised trials. Lancet 387, 17231731 (2016).
Article PubMed Google Scholar
Albers, G. W. et al. Thrombectomy for stroke at 6 to 16 hours with selection by perfusion imaging. N. Engl. J. Med. 378, 708718 (2018).
Article PubMed PubMed Central Google Scholar
Nogueira, R. G. et al. Thrombectomy 6 to 24 hours after stroke with a mismatch between deficit and infarct. N. Engl. J. Med. 378, 1121 (2018).
Article PubMed Google Scholar
Quinn, T., Dawson, J., Walters, M. & Lees, K. Functional outcome measures in contemporary stroke trials. Int. J. Stroke 4, 200205 (2009).
Article CAS PubMed Google Scholar
Johnston, K. C., Wagner, D. P., Haley, E. C. Jr. & Connors, A. F. Jr. Combined clinical and imaging information as an early stroke outcome measure. Stroke 33, 466472 (2002).
Article PubMed PubMed Central Google Scholar
Asadi, H., Dowling, R., Yan, B. & Mitchell, P. Machine learning for outcome prediction of acute ischemic stroke post intra-arterial therapy. PLoS ONE 9, e88225 (2014).
Article ADS PubMed PubMed Central Google Scholar
Monteiro, M. et al. Using machine learning to improve the prediction of functional outcome in ischemic stroke patients. IEEE/ACM Trans. Comput. Biol. Bioinf. 15, 19531959 (2018).
Article Google Scholar
Heo, J. et al. Machine learning-based model for prediction of outcomes in acute stroke. Stroke 50, 12631265 (2019).
Article PubMed Google Scholar
Bacchi, S. et al. Deep learning in the prediction of Ischaemic stroke thrombolysis functional outcomes: A pilot study. Acad. Radiol. 27, e19e23 (2020).
Article PubMed Google Scholar
Alaka, S. A. et al. Functional outcome prediction in ischemic stroke: A comparison of machine learning algorithms and regression models. Front. Neurol. 11, 889 (2020).
Article PubMed PubMed Central Google Scholar
Begoli, E., Bhattacharya, T. & Kusnezov, D. The need for uncertainty quantification in machine-assisted medical decision making. Nat. Mach. Intell. 1, 2023 (2019).
Article Google Scholar
Kim, D.-Y. et al. Deep learning-based personalised outcome prediction after acute ischaemic stroke. J. Neurol. Neurosurg. Psychiatry 94, 369378 (2023).
Article PubMed Google Scholar
Vora, N. A. et al. A 5-item scale to predict stroke outcome after cortical middle cerebral artery territory infarction: Validation from results of the diffusion and perfusion imaging evaluation for understanding stroke evolution (defuse) study. Stroke 42, 645649 (2011).
Article PubMed Google Scholar
Panni, P. et al. Acute stroke with large ischemic core treated by thrombectomy: Predictors of good outcome and mortality. Stroke 50, 11641171 (2019).
Article PubMed Google Scholar
Van Os, H. J. et al. Predicting outcome of endovascular treatment for acute ischemic stroke: Potential value of machine learning algorithms. Front. Neurol. 9, 784 (2018).
Article PubMed PubMed Central Google Scholar
Xie, Y. et al. Use of gradient boosting machine learning to predict patient outcome in acute ischemic stroke on the basis of imaging, demographic, and clinical information. Am. J. Roentgenol. 212, 4451 (2019).
Article Google Scholar
Thakkar, H. K., Liao, W.-W., Wu, C.-Y., Hsieh, Y.-W. & Lee, T.-H. Predicting clinically significant motor function improvement after contemporary task-oriented interventions using machine learning approaches. J. Neuroeng. Rehabil. 17, 110 (2020).
Article Google Scholar
Shao, H. et al. A new machine learning algorithm with high interpretability for improving the safety and efficiency of thrombolysis for stroke patients: A hospital-based pilot study. Digit. Health 9, 20552076221149530 (2023).
PubMed PubMed Central Google Scholar
Bronstein, M. M., Bruna, J., LeCun, Y., Szlam, A. & Vandergheynst, P. Geometric deep learning: Going beyond Euclidean data. IEEE Signal Process. Mag. 34, 1842 (2017).
Article ADS Google Scholar
Parisot, S. et al. Spectral graph convolutions for population-based disease prediction. In International Conference on Medical Image Computing and Computer-Assisted Intervention (eds Parisot, S. et al.) 177185 (Springer, 2017).
Google Scholar
Kazi, A. et al. Inceptiongcn: Receptive field aware graph convolutional network for disease prediction. In International Conference on Information Processing in Medical Imaging (eds Kazi, A. et al.) 7385 (Springer, 2019).
Chapter Google Scholar
Ravindra, N., Sehanobish, A., Pappalardo, J.L., Hafler, D.A. & van Dijk, D. Disease state prediction from single-cell data using graph attention networks. In: Proc. of the ACM conference on health, inference, and learning, 121130 (2020).
Huang, Y. & Chung, A. C. Disease prediction with edge-variational graph convolutional networks. Med. Image Anal. 77, 102375 (2022).
Article PubMed Google Scholar
Loftus, T. J. et al. Uncertainty-aware deep learning in healthcare: A scoping review. PLOS Digit. Health 1, e0000085 (2022).
Article PubMed PubMed Central Google Scholar
Abdar, M. et al. A review of uncertainty quantification in deep learning: Techniques, applications and challenges. Information Fusion 76, 243297 (2021).
Article Google Scholar
Abdar, M., Khosravi, A., Islam, S. M. S., Acharya, U. R. & Vasilakos, A. V. The need for quantification of uncertainty in artificial intelligence for clinical data analysis: Increasing the level of trust in the decision-making process. IEEE Syst. Man Cybern. Magaz. 8, 2840 (2022).
Article Google Scholar
Guo, C., Pleiss, G., Sun, Y. & Weinberger, K. Q. On calibration of modern neural networks. In Proceedings of the 34th International Conference on Machine Learning Vol. 70 (eds Precup, D. & Teh, Y. W.) 13211330 (PMLR, 2017).
Google Scholar
Pearce, T., Brintrup, A. & Zhu, J. Understanding softmax confidence and uncertainty. Preprint at arXiv:2106.04972 (2021).
Alarab, I., Prakoonwit, S. & Nacer, M. I. Illustrative discussion of mc-dropout in general dataset: Uncertainty estimation in bitcoin. Neural Process. Lett. 53, 10011011 (2021).
Article Google Scholar
Alarab, I. & Prakoonwit, S. Uncertainty estimation-based adversarial attacks: a viable approach for graph neural networks. Soft Computing 113 (2023).
Gal, Y. & Ghahramani, Z. Dropout as a Bayesian approximation: Representing model uncertainty in deep learning. In International Conference on Machine Learning (eds Gal, Y. & Ghahramani, Z.) 10501059 (PMLR, 2016).
Google Scholar
Singer, O. C. et al. Collateral vessels in proximal middle cerebral artery occlusion: The endostroke study. Radiology 274, 851858 (2015).
Article PubMed Google Scholar
Bang, O. Y. et al. Impact of collateral flow on tissue fate in acute Ischaemic stroke. J. Neurol. Neurosurg. Psychiatry 79, 625629 (2008).
Article CAS PubMed Google Scholar
Menon, B. K. et al. Assessment of leptomeningeal collaterals using dynamic ct angiography in patients with acute ischemic stroke. J. Cerebral Blood Flow Metabol. 33, 365371 (2013).
Article Google Scholar
Berkhemer, O. A. et al. Collateral status on baseline computed tomographic angiography and intra-arterial treatment effect in patients with proximal anterior circulation stroke. Stroke 47, 768776 (2016).
Article CAS PubMed Google Scholar
Menon, B. et al. Regional leptomeningeal score on ct angiography predicts clinical and imaging outcomes in patients with acute anterior circulation occlusions. Am. J. Neuroradiol. 32, 16401645 (2011).
Article CAS PubMed PubMed Central Google Scholar
Kucinski, T. et al. Collateral circulation is an independent radiological predictor of outcome after thrombolysis in acute ischaemic stroke. Neuroradiology 45, 1118 (2003).
Article CAS PubMed Google Scholar
Sheth, S. A. et al. Collateral flow as causative of good outcomes in endovascular stroke therapy. J. Neurointerv. Surg. 8, 27 (2016).
Article PubMed Google Scholar
Seyman, E. et al. The collateral circulation determines cortical infarct volume in anterior circulation ischemic stroke. BMC Neurol. 16, 19 (2016).
Article Google Scholar
Elijovich, L. et al. Cta collateral score predicts infarct volume and clinical outcome after endovascular therapy for acute ischemic stroke: a retrospective chart review. J. Neurointerv. Surg. 8, 559562 (2016).
Article PubMed Google Scholar
Prasetya, H. et al. Value of ct perfusion for collateral status assessment in patients with acute ischemic stroke. Diagnostics 12, 3014 (2022).
Article PubMed PubMed Central Google Scholar
Potreck, A. et al. Rapid ct perfusion-based relative cbf identifies good collateral status better than hypoperfusion intensity ratio, cbv-index, and time-to-maximum in anterior circulation stroke. Am. J. Neuroradiol. 43, 960965 (2022).
Article CAS PubMed PubMed Central Google Scholar
Olivot, J. M. et al. Hypoperfusion intensity ratio predicts infarct progression and functional outcome in the defuse 2 cohort. Stroke 45, 10181023 (2014).
Article PubMed PubMed Central Google Scholar
Li, B.-H. et al. Cerebral blood volume index may be a predictor of independent outcome of thrombectomy in stroke patients with low aspects. J. Clin. Neurosci. 103, 188192 (2022).
Article ADS PubMed Google Scholar
Laredo, C. et al. Clinical and therapeutic variables may influence the association between infarct core predicted by ct perfusion and clinical outcome in acute stroke. Eur. Radiol. 32, 45104520 (2022).
Article CAS PubMed Google Scholar
Christodoulou, E. et al. A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models. J. Clin. Epidemiol. 110, 1222 (2019).
Article PubMed Google Scholar
Ramos, L. A. et al. Predicting poor outcome before endovascular treatment in patients with acute ischemic stroke. Front. Neurol. 11, 580957 (2020).
Article PubMed PubMed Central Google Scholar
Leker, R. R. et al. Post-stroke aspects predicts outcome after thrombectomy. Neuroradiology 63, 769775 (2021).
Article PubMed Google Scholar
Peng, H., Long, F. & Ding, C. Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy. IEEE Trans. Pattern Anal. Mach. Intell. 27, 12261238 (2005).
Article PubMed Google Scholar
Zhao, Z., Anand, R. & Wang, M. Maximum relevance and minimum redundancy feature selection methods for a marketing machine learning platform. In 2019 IEEE International Conference on Data Science and Advanced Analytics (DSAA) (eds Zhao, Z. et al.) 442452 (IEEE, 2019).
Chapter Google Scholar
Paszke, A. et al. Pytorch: An imperative style, high-performance deep learning library. In Advances in Neural Information Processing Systems Vol. 32 (eds Paszke, A. et al.) 80248035 (Curran Associates, Inc., 2019).
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