Abstract
The unusual functionality of the brain, which distracts and causes hazardous problems in the brain, is Alzheimer’s disease (AD). For decades, the level of research and identifying the disease in early stages are very less. To overcome this problem, we had introduced machine learning methods which are dedicated to the early identification of AD along with predictions of its progression in mild cognitive impairment. Alzheimer’s Disease Neuroimaging Initiative (ADNI) is used for the gathering of information. A few regions of research like multi-area examination of cross-sectional and longitudinal FDG-PET images provide some reliable source which is secured at a single time point is used to improve classification results similar to those gathered using data from research quality MRI.
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Enumula, R.R., Amudhavel, J. (2019). Alzheimer’s Ailment Prediction Using Neuroimage Based on Machine Learning Methods. In: Chaki, N., Devarakonda, N., Sarkar, A., Debnath, N. (eds) Proceedings of International Conference on Computational Intelligence and Data Engineering. Lecture Notes on Data Engineering and Communications Technologies, vol 28. Springer, Singapore. https://doi.org/10.1007/978-981-13-6459-4_10
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DOI: https://doi.org/10.1007/978-981-13-6459-4_10
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