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Research Article

A novel solution of an elastic net regularisation for dementia knowledge discovery using deep learning

, , , ORCID Icon, , & show all
Pages 807-829 | Received 01 Nov 2019, Accepted 31 May 2021, Published online: 05 Sep 2021

References

  • Akinori, H., Masaki, M., Jun, I., Li-Juan, M., Hui-Yu, B., Bao-Shuai, S., & Masatsugu, H. (2018). Predicting outcome of Morris water maze test in vascular dementia mouse model with deep learning. PLoS ONE, 12(2), 1–12.
  • Chaddad, A., Desrosiers, C., & Niazi, T. (2018). Deep Radiomic Analysis of MRI Related to Alzheimer’s Disease. IEEE Access, 6, 58213–58221. https://doi.org/10.1109/ACCESS.2018.2871977
  • Choi, H., Choe, J. Y., Kim, H., Han, J. W., Chi, Y. K., Kim, K., & Kim, K. W. (2018). Deep learning based low-cost high-accuracy diagnostic framework for dementia using comprehensive neuropsychological assessment profiles. BMC Geriatrics, 18(1). https://doi.org/10.1186/s12877-018-0915-z
  • Choi, H., & Jin, K. H. (2018). Predicting cognitive decline with deep learning of brain metabolism and amyloid imaging. Behavioural Brain Research, 344, 103–109. https://doi.org/10.1016/j.bbr.2018.02.017
  • Ding, J., Li, S., Wang, Z., Jiang, Z., & Zhao, Y. (2018). Brain MRI imaging mechanism based on deep visual information perception and dementia degree induction. Multimedia Tools and Applications, 1–19.
  • Huang, W., Zeng, J., Wan, C., Ding, H., & Chen, G. Image-based dementia disease diagnosis via deep low-resource pair-wise learning. (2018). Multimedia Tools and Applications. 77(14). 18763–18780. G. & Chen. https://doi.org/10.1007/s11042-017-4492-5
  • Ieracitano, C., Mammone, N., Bramanti, A., Hussain, A., & Morabito, F. C. (2018). Convolutional Neural Network approach for classification of dementia stages based on 2D-spectral representation of EEG recordings,”. Neurocomputing, 323, 96–107. https://doi.org/10.1016/j.neucom.2018.09.071
  • Ju, R., Hu, C., zhou, P., & Li, Q. (2017). Early Diagnosis of Alzheimer’s Disease Based on Resting-State Brain Networks and Deep Learning. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 1(1).
  • Langavant, L. D., Bayen, E., & Yaffe, K. (2018). Unsupervised Machine Learning to Identify High Likelihood of Dementia in Population-Based Surveys: Development and Validation Study. Journal of Medical Internet Research, 20(7).
  • Lee, J. E., Jeong, D. U., Lee, J., Chang, W. S., & Chang, J. W. (2016). The effect of nucleus basalis magnocellularis deep brain stimulation on memory function in a rat model of dementia. BMC Neurology, 16(1), 1–9. https://doi.org/10.1186/s12883-016-0529-z
  • Liu, J., Shang, S., Zheng, K., & Wen, J. (2016). Multi-view ensemble learning for dementia diagnosis from neuroimaging: An artificial neural network approach. Neurocomputing, 195, 112–116. https://doi.org/10.1016/j.neucom.2015.09.119
  • Liu, M., Zhang, J., Adeli, E., & Shen, D. (2018). Joint Classification and Regression via Deep Multi-Task Multi-Channel Learning for Alzheimer’s Disease Diagnosis. IEEE Transactions on Bio-medical Engineering, 11(1).
  • Niessen, W. J. (2016). MR brain image analysis in dementia: From quantitative imaging biomarkers to ageing brain models and imaging genetics. Medical Image Analysis, 33, 107–113. https://doi.org/10.1016/j.media.2016.06.029
  • Tang, Y., Michael, W. L., & Xing, Y. (2018). “A systems‐based model of Alzheimer’s disease “, Alzheimer’s & Dementia. The Journal of the Alzheimer’s Association, 15(1), 168–171. https://doi.org/10.1016/j.jalz.2018.06.3058
  • TANVEER, M., RICHHARIYA, B., & KHAN, R. U. (2019). “Machine learning techniques for the diagnosis of Alzheimer’s disease: Areview “, ACM Transactions on Multimedia Computing, Communications and Applications. Appl, 37(4), 111.
  • Weiming, L., Tong, T., Qinquan, G., Di, G., Xiaofeng, D., Yonggui, Y., & Xiaobo, Q. (2018). Convolutional Neural Networks-Based MRI Image Analysis for the Alzheimer’s Disease Prediction From Mild Cognitive Impairment. Frontiers in Neuroscience, 12(777).
  • Zhou, T., Thung, K.-H., Zhu, X., & Shen, D. (2018). Effective feature learning and fusion of multimodality data using stage-wise deep neural network for dementia diagnosis. Human Brain Mapping.

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