Machine Learning Approach to Improve Prediction Accuracy of Alzheimer’s Disease

Authors

  • Chaiyaporn Mutsalklisana Northeastern University, Graduate School of Engineering, Information Systems Program, 130 Snell Engineering Center, 360 Huntington Avenue, Boston 02115, USA
  • Kishore Mohan Northeastern University, Graduate School of Engineering, Information Systems Program, 130 Snell Engineering Center, 360 Huntington Avenue, Boston 02115, USA
  • Akshaya Nagarajan Northeastern University, Graduate School of Engineering, Information Systems Program, 130 Snell Engineering Center, 360 Huntington Avenue, Boston 02115, USA
  • Priyanka Mishra Northeastern University, Graduate School of Engineering, Information Systems Program, 130 Snell Engineering Center, 360 Huntington Avenue, Boston 02115, USA

Keywords:

Alzheimer’s medical care, Machine Learning approach to improve prediction accuracy, Integrating neuroimaging, neuropsychological, neurochemical and neurogenetics results for effective assessment.

Abstract

Alzheimer’s is a chronic neurodegenerative disease developed due to multiple cognitive deficits that progressively leads to at least one of the following: apraxia, aphasia, agnosia or a disturbance in executive functioning. As of 2012, more than 5.1 million Americans are affected by Alzheimer’s. Alzheimer’s disease accounts for 60 to 80 percent of dementia cases. Numerous pharmaceutical market leaders attempt on developing a cure for the disease. Significant progress has been made on this field. However, studies have shown that manual assessment of the disease using various parameters including (but not restricted to) Neuroimaging (MRI, PET, etc.), Neuropsychological tests (MMSE, FAQ, GDS, NPI, etc.) and Neurogenetics (TOMM40 gene assessment) yield an accuracy of 96% only. Our study involved integrating all three results and allowing the system to predict whether a patient is suffering from Alzheimer's.

References

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Published

2016-05-25

How to Cite

Mutsalklisana, C., Mohan, K., Nagarajan, A., & Mishra, P. (2016). Machine Learning Approach to Improve Prediction Accuracy of Alzheimer’s Disease. American Scientific Research Journal for Engineering, Technology, and Sciences, 20(1), 1–8. Retrieved from https://asrjetsjournal.org/index.php/American_Scientific_Journal/article/view/1634

Issue

Vol. 20 No. 1 (2016)

Section

Articles

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