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Md Easin Hasan and Amy Wagler
Neuroimaging experts in biotech industries can benefit from using cutting-edge artificial intelligence techniques for Alzheimer?s disease (AD)- and dementia-stage prediction, even though it is difficult to anticipate the precise stage of dementia and AD....
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Vera Afreixo, Ana Helena Tavares, Vera Enes, Miguel Pinheiro, Leonor Rodrigues and Gabriela Moura
In this work, we aimed to establish a stable and accurate procedure with which to perform feature selection in datasets with a much higher number of predictors than individuals, as in genome-wide association studies. Due to the instability of feature sel...
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Muhammad Irfan, Seyed Shahrestani and Mahmoud Elkhodr
Dementia, including Alzheimer?s Disease (AD), is a complex condition, and early detection remains a formidable challenge due to limited patient records and uncertainty in identifying relevant features. This paper proposes a machine learning approach to a...
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Michal Brzus, Kevin Knoernschild, Jessica C. Sieren and Hans J. Johnson
Translation of basic animal research to find effective methods of diagnosing and treating human neurological disorders requires parallel analysis infrastructures. Small animals such as mice provide exploratory animal disease models. However, many interve...
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Zhiqiong Wang, Zican Lin, Shuo Li, Yibo Wang, Weiying Zhong, Xinlei Wang and Junchang Xin
Alzheimer?s disease (AD) is a progressive, irreversible neurodegenerative disorder that requires early diagnosis for timely treatment. Functional magnetic resonance imaging (fMRI) is a non-invasive neuroimaging technique for detecting brain activity. To ...
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Xiaoli Yang, Yuxin Xia, Zhenwei Li, Lipei Liu, Zhipeng Fan and Jiayi Zhou
Alzheimer?s disease (AD) is one of the most common irreversible brain diseases in the elderly. Mild cognitive impairment (MCI) is an early symptom of AD, and the early intervention of MCI may slow down the progress of AD. However, due to the subtle neuro...
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Xibin Wang, Qiong Zhou, Hui Li and Mei Chen
Imbalanced learning problems often occur in application scenarios and are additionally an important research direction in the field of machine learning. Traditional classifiers are substantially less effective for datasets with an imbalanced distribution...
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Juan Jiang, Hong Liu, Xin Yu, Jin Zhang, Bing Xiong and Lidan Kuang
Precisely segmenting the hippocampus from the brain is crucial for diagnosing neurodegenerative illnesses such as Alzheimer?s disease, depression, etc. In this research, we propose an enhanced hippocampus segmentation algorithm based on 3D U-Net that can...
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Nayef Alqahtani, Shadab Alam, Ibrahim Aqeel, Mohammed Shuaib, Ibrahim Mohsen Khormi, Surbhi Bhatia Khan and Areej A. Malibari
Dementias that develop in older people test the limits of modern medicine. As far as dementia in older people goes, Alzheimer?s disease (AD) is by far the most prevalent form. For over fifty years, medical and exclusion criteria were used to diagnose AD,...
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Wieslaw L. Nowinski
Although no dataset at the nanoscale for the entire human brain has yet been acquired and neither a nanoscale human whole brain atlas has been constructed, tremendous progress in neuroimaging and high-performance computing makes them feasible in the non-...
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