CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

New Approach for Clinical Decision Support System of Alzheimer’s Disease Diagnosis

by Zouhour Maâtar, Chokri Abdelmoula, Mohamed Masmoudi
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 177 - Number 20
Year of Publication: 2019
Authors: Zouhour Maâtar, Chokri Abdelmoula, Mohamed Masmoudi
10.5120/ijca2019919639

Zouhour Maâtar, Chokri Abdelmoula, Mohamed Masmoudi . New Approach for Clinical Decision Support System of Alzheimer’s Disease Diagnosis. International Journal of Computer Applications. 177, 20 ( Nov 2019), 39-43. DOI=10.5120/ijca2019919639

@article{ 10.5120/ijca2019919639,
author = { Zouhour Maâtar, Chokri Abdelmoula, Mohamed Masmoudi },
title = { New Approach for Clinical Decision Support System of Alzheimer’s Disease Diagnosis },
journal = { International Journal of Computer Applications },
issue_date = { Nov 2019 },
volume = { 177 },
number = { 20 },
month = { Nov },
year = { 2019 },
issn = { 0975-8887 },
pages = { 39-43 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume177/number20/31017-2019919639/ },
doi = { 10.5120/ijca2019919639 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:46:27.718707+05:30
%A Zouhour Maâtar
%A Chokri Abdelmoula
%A Mohamed Masmoudi
%T New Approach for Clinical Decision Support System of Alzheimer’s Disease Diagnosis
%J International Journal of Computer Applications
%@ 0975-8887
%V 177
%N 20
%P 39-43
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Alzheimer’s disease is a chronic dementia. It destroys gradually the memory and get worse over time. The diagnosis of AD is generally made very late. The great challenge is reaching an early and accurate diagnosis. In this case, a Clinical Decision Support System (CDSS) to help physicians diagnose AD and related disorders: mild cognitive impairment (MCI) and Dementia (D) is proposed. The originality of the idea is that many parameters are included such as cognitive test scores, neurological, biological, clinical and demographic data and this is in order to carry on the most accurate diagnosis for every subject. The Support Vector Machine showed that the proposed CDSS decision model achieves good performance.

References
  1. M. J. Prince, F.Wu, Y. Guo et al., “The burden of disease in older people and implications for health policy and practice,” The Lancet, vol. 385, no. 9967, pp. 549–562, 2015.
  2. M. Prince, A. Wimo, M. Guerchet, A. Gemma-Claire, Y.-T. Wu, and M. Prina, “World Alzheimer Report 2015: The Global Impact of Dementia - An analysis of prevalence, incidence, cost and trends,”Alzheimer’s Dis. Int., p. 84, 2015.
  3. Hajem S, Saidi O, Ben Mansour N, Mejdoub Y, Hsairi M. Epidemiology of dementias in Tunisia. NPG Neurology - Psychiatry - Geriatrics. 2014; 14 (84): 326-33.
  4. E. S. Berner, Clinical Decision Support Systems Theory and Practice. s.l.: Springer-Verlag, 2016.
  5. R.B. Haynes, and N. L Wilczynski, “Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: Methods of a decision-maker researcher partnership systematic review”, Implement Sci, vol. 5(1), n° 12, 2010.
  6. A.Weakley J. A.Williams, M. Schmitter-Edgecombe, and D. J.Cook, “Neuropsychological test selection for cognitive impairment classification: a machine learning approach,” Journal of Clinical and Experimental Neuropsychology, vol. 37, no. 9, pp.899–916, 2015.
  7. M.-F.Lou, Y.-T. Dai, G.-S. Huang, and P.-J. Yu, “Identifying the most efficient items from the Mini-Mental State Examination for cognitive function assessment in older Taiwanese patients, ”Journal of Clinical Nursing, vol. 16, no. 3, pp. 502–508, 2007.
  8. C.-Y. Chen, K.-K. Leung, and C.-Y. Chen, “A quick dementia screening tool for primary care physicians,” Archives of Gerontology and Geriatrics, vol. 53, no. 1, pp. 100–103, 2011.
  9. Tierney, M., Szalai, J., Snow, W., Fisher, R., Nores, A., Nadon, G., Dunn, E., and George-Hyslop, P. S., Prediction of probable Alzheimer’s disease in memory-impaired patients a prospective longitudinal study. Neurology 46(3):661–665, 1996.
  10. P. R. Pinheiro, A. Castro, and M. Pinheiro, “A multicriteria model applied in the diagnosis of Alzheimer’s disease: A Bayesian network”, In: Proceedings of 11thIEEE International Conference.
  11. R. Chaves, J. Ramırez, J. M. Gorriz et al., “SVM-based computer- aided diagnosis of the Alzheimer’s disease using test NMSE feature selection with feature correlation weighting,” Neuroscience Letters, vol. 461, no. 3, pp. 293–297, 2009.
  12. J. Ramırez, J. M. Gorriz, F. Segovia et al., “Computer aided diagnosis system for the Alzheimer’s disease based on partial least squares and random forest SPECT image classification,”Neuroscience Letters, vol. 472, no. 2, pp. 99–103, 2010.
  13. Polikar,Robi,et al. "Multimodal EEG, MRI and PET data fusion for Alzheimer's disease diagnosis." Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE. IEEE, 2010.
  14. Zhang Y, Dong A, Philips P, et al. Detection of subjects and brain regions related to Alzheimer's disease using 3D MRI scans based on Eigen-brain and machine learning. Front Computer Neuroscience. 2015; 9:66.
  15. Xiaofeng R. et al., “Finding people in archive films through tracking”, Computer Vision and Pattern Recognition, 2008.CVPR 2008.
Index Terms

Computer Science
Information Sciences

Keywords

Alzheimer’s disease (AD) Dementia Clinical Decision Support System (CDSS) cognitive test

Powered by PhDFocusTM