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RETRACTION: Embedded web medical system and rehabilitation nursing of ischemic stroke (Retraction of Vol 81, art no 103674, 2021)
被引：1
|作者：
Din, Sadia
机构：
[1] Department of Rehabilitation Medicine, Jining First People's Hospital, Jining, 272100, Shandong
[2] Department of Sleep Medicine, Jining First People's Hospital, Jining, 272100, Shandong
[3] Department of Acupuncture and Physiotherapy, Jining First People's Hospital, Jining, 272100, Shandong
[4] Neurosurgery, Jining First People's Hospital, Jining, 272100, Shandong
[5] Postpartum Rhabilitation, Rencheng District Maternal and Child Health Hospital, Jining, 272100, Shandong
关键词：
Artificial Neural Network (ANN) classification;
Data acquisition and preprocessing;
Ischemic Stroke;
Web medical system;
D O I：
10.1016/j.micpro.2020.103674
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
The subtype of ischemic stroke is valuable for highly effective interventions and treatments and essential for the prognosis of ischemic stroke. The judgment of illness grouping manuals is tedious, mistake inclined, and the constraint of scaling to enormous informational indexes. This investigation utilized the subtype order of ischemic stroke dependent on the International Stroke Trial (IST) dataset across the board learning strategy. It looks at basic issues in element choice and forecast of clinical datasets. First, the Pearson correlation between the Shapiro-Wilk algorithm ranking and analytical capabilities is determined by the importance of functionality. The segmented images are then classified using the Artificial Neural Network (ANN) for pathological and normal output brain images. Effective Artificial Neural Networks (ANNs), classifications, have been proposed for brain tumor detection based on different digital image processing steps. Therefore, ANN results have been tested and classified using FPGA Xilinx software. © 2020
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