A supervised method to assist the diagnosis of Alzheimer's Disease based on functional Magnetic Resonance Imaging
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Publisher
IEEE
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http://xplorestaging.ieee.org/ielx5/4352184/4352185/04353067.pdf?arnumber=4353067
Cited by 9 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. Machine Learning for Interpretation of Brain Images: A Detailed Analysis through survey;2021 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS);2021-02-19
2. Random forest feature selection, fusion and ensemble strategy: Combining multiple morphological MRI measures to discriminate among healhy elderly, MCI, cMCI and alzheimer’s disease patients: From the alzheimer’s disease neuroimaging initiative (ADNI) database;Journal of Neuroscience Methods;2018-05
3. An Ensemble of Classifiers based Approach for Prediction of Alzheimer's Disease using fMRI Images based on Fusion of Volumetric, Textural and Hemodynamic Features;Advances in Electrical and Computer Engineering;2018
4. How random is the random forest? Random forest algorithm on the service of structural imaging biomarkers for Alzheimer's disease: from Alzheimer's disease neuroimaging initiative (ADNI) database;Neural Regeneration Research;2018
5. Random Forest Algorithm for the Classification of Neuroimaging Data in Alzheimer's Disease: A Systematic Review;Frontiers in Aging Neuroscience;2017-10-06
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