Radiomics features as predictors to distinguish fast and slow progression of Mild Cognitive Impairment to Alzheimer's disease-Reference-Cited by-同舟云学术

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Radiomics features as predictors to distinguish fast and slow progression of Mild Cognitive Impairment to Alzheimer's disease

Published:2018-07 Issue: Volume: Page:
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Container-title:2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
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Author:

Li Yupeng,Jiang Jiehui,Shen Ting,Wu Ping,Zuo Chuantao

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8471725/8512178/08512273.pdf?arnumber=8512273

Cited by 19 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Detailed study on Image Segmentation with Different Optimization Algorithms for Dementia Disease;2023 International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication Engineering (RMKMATE);2023-11-01

2. Performance of hippocampal radiomics models based on T2-FLAIR images in mesial temporal lobe epilepsy with hippocampal sclerosis;European Journal of Radiology;2023-10

3. Radiomics and Artificial Intelligence for the Diagnosis and Monitoring of Alzheimer’s Disease: A Systematic Review of Studies in the Field;Journal of Clinical Medicine;2023-08-21

4. Do radiomics or diffusion-tensor images provide additional information to predict brain amyloid-beta positivity?;Scientific Reports;2023-06-16

5. Prediction of Alzheimer’s Using Random Forest with Radiomic Features;Computer Systems Science and Engineering;2023

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