2021
DOI: 10.1007/978-3-030-86993-9_33
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D3mciAD: Data-Driven Diagnosis of Mild Cognitive Impairment Utilizing Syntactic Images Generation and Neural Nets

Abstract: Alzheimer's disease, an incurable chronic neurological disorder (NLD) that affects human memory and demises cognitive thinking ability with shrinkage of the brain area. Early detection of Alzheimer's disease (AD) is the only hope to delay its effect. This study designed a computer-aided automated detection method that can detect mild cognitive impairment for AD from magnetic resonance image scans. The datadriven solution approach requires an extensive quantity of annotated images for diagnosis. However, obtain… Show more

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Cited by 3 publications
(2 citation statements)
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“…As shown in Table 8, the two algorithms proposed in this paper have improved the classification results for different levels of Alzheimer's disease compared with the methods proposed by previous researchers (Liu and Shen, 2014;Sarraf and Tofighi, 2016;De Luna and Marcia, 2021;Hasan et al, 2021;Xu, 2021), while this paper extends the classification between the two previously studied diseases to three categories and achieves better classification results. Among them, Sarraf et al used the classical architecture LeNet-5 to classify functional MRI data of AD subjects with normal controls, and the accuracy of the tested…”
Section: Comparison With Other Methodsmentioning
confidence: 71%
“…As shown in Table 8, the two algorithms proposed in this paper have improved the classification results for different levels of Alzheimer's disease compared with the methods proposed by previous researchers (Liu and Shen, 2014;Sarraf and Tofighi, 2016;De Luna and Marcia, 2021;Hasan et al, 2021;Xu, 2021), while this paper extends the classification between the two previously studied diseases to three categories and achieves better classification results. Among them, Sarraf et al used the classical architecture LeNet-5 to classify functional MRI data of AD subjects with normal controls, and the accuracy of the tested…”
Section: Comparison With Other Methodsmentioning
confidence: 71%
“…Recently, different types of artificial intelligence (AI) techniques, like deep learning (DL) and machine learning (ML), have been used in medicine to create safe, low-cost, and automatic ways to diagnose diseases like cancer, tuberculosis, diabetic foot ulcers, brain tumors, and more [ [8] , [9] , [10] , [11] , [12] ]. In the field of medical image processing, various DL-based segmentation algorithms like thresholding, watersheds, region growth, etc.…”
Section: Introductionmentioning
confidence: 99%