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Artificial intelligence (AI), a computer system aiming to mimic human intelligence, is gaining increasing interest and is being incorporated into many fields, including medicine. Stroke medicine is one such area of application of AI, for improving the accuracy of diagnosis and the quality of patient care. For stroke management, adequate analysis of stroke imaging is crucial. Recently, AItechniques have been applied to decipher the data from stroke imaging and have demonstrated some promising results. In the very near future, such AI techniques may play a pivotal role in determining the therapeutic methods and predicting the prognosis for stroke patients in an individualized manner. In this review, we offer a glimpse at the use of AI in stroke imaging, specifically focusing on its technical principles, clinical application, and future perspectives.
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참고문헌 (26)
참고문헌 신청
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Chen Y / 2016 / Automated quantification of cerebral edema following hemispheric infarction: application of a machine-learning algorithm to evaluate CSF shifts on serial hea
Cortes C / 1995 / Support-vector networks / Mach Learn 20 : 273 ~ 297
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Chen L / 2017 / Fully automatic acute ischemic lesion segmentation in DWI using convolutional neural networks / Neuroimage Clin 15 : 633 ~ 643
Chen Y / 2016 / Automated quantification of cerebral edema following hemispheric infarction: application of a machine-learning algorithm to evaluate CSF shifts on serial hea
Cortes C / 1995 / Support-vector networks / Mach Learn 20 : 273 ~ 297
Dhar R / 2016 / CSF volumetric analysis for quantification of cerebral edema after hemispheric infarction / Neurocrit Care 24 : 420 ~ 427
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