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Editorial
. 2020 Jun;295(3):638-639.
doi: 10.1148/radiol.2020200819. Epub 2020 Apr 7.

Fellow in a Box: Combining AI and Domain Knowledge with Bayesian Networks for Differential Diagnosis in Neuroimaging

Greg Zaharchuk  1
Affiliations
Editorial

Fellow in a Box: Combining AI and Domain Knowledge with Bayesian Networks for Differential Diagnosis in Neuroimaging

Greg Zaharchuk. Radiology. 2020 Jun.
No abstract available

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Dr Zaharchuk is a professor of radiology at Stanford University in the division of neuroimaging. He received his MD degree from Harvard Medical School and his PhD degree from the Harvard-MIT Health Sciences and Technology program, with clinical training at the University of California, San Francisco. He directs the Center for Advanced Functional Neuroimaging at Stanford University, where his research focuses on advanced medical imaging techniques and algorithms (including AI) with the goal of alleviating the burden of neurologic disease.
Dr Zaharchuk is a professor of radiology at Stanford University in the division of neuroimaging. He received his MD degree from Harvard Medical School and his PhD degree from the Harvard-MIT Health Sciences and Technology program, with clinical training at the University of California, San Francisco. He directs the Center for Advanced Functional Neuroimaging at Stanford University, where his research focuses on advanced medical imaging techniques and algorithms (including AI) with the goal of alleviating the burden of neurologic disease.
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References

    1. Krizhevsky A, Sutskever I, Hinton GE. ImageNet classification with deep convolutional neural networks. NIPS’12: Proceedings of the 25th International Conference on Neural Information Processing Systems, 2012; 1097–1105.
    1. Rauschecker AM, Rudie JD, Xie L, et al. Artificial Intelligence System Approaching Neuroradiologist-level Differential Diagnosis Accuracy at Brain MRI. Radiology 2020;295:626–637. - PMC - PubMed
    1. Korfiatis P, Kline TL, Erickson BJ. Automated segmentation of hyperintense regions in FLAIR MRI using deep learning. Tomography 2016;2(4):334–340. - PMC - PubMed
    1. Pereira S, Pinto A, Alves V, Silva CA. Brain tumor segmentation using convolutional neural networks in MRI images. IEEE Trans Med Imaging 2016;35(5):1240–1251. - PubMed
    1. Menze BH, Jakab A, Bauer S, et al. The multimodal brain tumor image segmentation benchmark (BRATS). IEEE Trans Med Imaging 2015;34(10):1993–2024. - PMC - PubMed

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