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Title: :  EARLY DETECTION OF ALZHEIMER’S DISEASE PROGRESSION WITH MULTI-MODAL BRAIN IMAGING AND CLINICAL DATA
PaperId: :  23047
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 10 Issue 2 2024
DUI:    16.0415/IJARIIE-23047
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
ABINESH ABannari Amman Institute Of Technology
GOWTHAM PRABHU PBannari Amman Institute Of Technology
KIRUBHAKARAN KBannari Amman Institute Of Technology
KALAIYARASI MBannari Amman Institute Of Technology

Abstract

Electronics And Communication Enginnering
Magnetic Resonance Imaging (MRI), CT Scan, and Convolutional Neural Network (CNN).
Early detection of Alzheimer's Disease (AD) progression is critical for timely intervention and management. This study proposes a novel approach employing multi-modal brain imaging data, specifically Magnetic Resonance Imaging (MRI), augmented with clinical data, to detect early signs of AD progression. The methodology relies on Convolutional Neural Networks (CNNs) to extract intricate features from MRI scans, capturing subtle structural changes indicative of AD progression. By training the CNN on a diverse dataset comprising MRI scans from individuals at varying stages of cognitive impairment and incorporating associated clinical data, including cognitive assessments and demographic information, our model gains a comprehensive understanding of AD progression. The integration of multi-modal imaging data and clinical information enhances the model's ability to detect subtle alterations in brain structure associated with AD progression. Through extensive experimentation and validation on independent datasets, our approach demonstrates promising results in early detection of AD progression, outperforming existing methods in terms of accuracy and sensitivity. This framework offers a non-invasive and scalable approach for early detection of AD progression, enabling timely interventions and personalized treatment strategies. By leveraging the complementary information provided by MRI and clinical data, our model provides valuable insights into disease progression, facilitating improved patient care and outcomes in the battle against Alzheimer's Disease. Keywords: Magnetic Resonance Imaging(MRI), CT scan, Convolutional Neural Network (CNN).

Citations

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IJARIIE ABINESH A, GOWTHAM PRABHU P, KIRUBHAKARAN K, and KALAIYARASI M. "EARLY DETECTION OF ALZHEIMER’S DISEASE PROGRESSION WITH MULTI-MODAL BRAIN IMAGING AND CLINICAL DATA" International Journal Of Advance Research And Innovative Ideas In Education Volume 10 Issue 2 2024 Page 2219-2224
MLA ABINESH A, GOWTHAM PRABHU P, KIRUBHAKARAN K, and KALAIYARASI M. "EARLY DETECTION OF ALZHEIMER’S DISEASE PROGRESSION WITH MULTI-MODAL BRAIN IMAGING AND CLINICAL DATA." International Journal Of Advance Research And Innovative Ideas In Education 10.2(2024) : 2219-2224.
APA ABINESH A, GOWTHAM PRABHU P, KIRUBHAKARAN K, & KALAIYARASI M. (2024). EARLY DETECTION OF ALZHEIMER’S DISEASE PROGRESSION WITH MULTI-MODAL BRAIN IMAGING AND CLINICAL DATA. International Journal Of Advance Research And Innovative Ideas In Education, 10(2), 2219-2224.
Chicago ABINESH A, GOWTHAM PRABHU P, KIRUBHAKARAN K, and KALAIYARASI M. "EARLY DETECTION OF ALZHEIMER’S DISEASE PROGRESSION WITH MULTI-MODAL BRAIN IMAGING AND CLINICAL DATA." International Journal Of Advance Research And Innovative Ideas In Education 10, no. 2 (2024) : 2219-2224.
Oxford ABINESH A, GOWTHAM PRABHU P, KIRUBHAKARAN K, and KALAIYARASI M. 'EARLY DETECTION OF ALZHEIMER’S DISEASE PROGRESSION WITH MULTI-MODAL BRAIN IMAGING AND CLINICAL DATA', International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 2, 2024, p. 2219-2224. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/EARLY_DETECTION_OF_ALZHEIMER’S_DISEASE_PROGRESSION_WITH_MULTI_MODAL_BRAIN_IMAGING_AND_CLINICAL_DATA_ijariie23047.pdf (Accessed : ).
Harvard ABINESH A, GOWTHAM PRABHU P, KIRUBHAKARAN K, and KALAIYARASI M. (2024) 'EARLY DETECTION OF ALZHEIMER’S DISEASE PROGRESSION WITH MULTI-MODAL BRAIN IMAGING AND CLINICAL DATA', International Journal Of Advance Research And Innovative Ideas In Education, 10(2), pp. 2219-2224IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/EARLY_DETECTION_OF_ALZHEIMER’S_DISEASE_PROGRESSION_WITH_MULTI_MODAL_BRAIN_IMAGING_AND_CLINICAL_DATA_ijariie23047.pdf (Accessed : )
IEEE ABINESH A, GOWTHAM PRABHU P, KIRUBHAKARAN K, and KALAIYARASI M, "EARLY DETECTION OF ALZHEIMER’S DISEASE PROGRESSION WITH MULTI-MODAL BRAIN IMAGING AND CLINICAL DATA," International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 2, pp. 2219-2224, Mar-App 2024. [Online]. Available: https://ijariie.com/AdminUploadPdf/EARLY_DETECTION_OF_ALZHEIMER’S_DISEASE_PROGRESSION_WITH_MULTI_MODAL_BRAIN_IMAGING_AND_CLINICAL_DATA_ijariie23047.pdf [Accessed : ].
Turabian ABINESH A, GOWTHAM PRABHU P, KIRUBHAKARAN K, and KALAIYARASI M. "EARLY DETECTION OF ALZHEIMER’S DISEASE PROGRESSION WITH MULTI-MODAL BRAIN IMAGING AND CLINICAL DATA." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 10 number 2 ().
Vancouver ABINESH A, GOWTHAM PRABHU P, KIRUBHAKARAN K, and KALAIYARASI M. EARLY DETECTION OF ALZHEIMER’S DISEASE PROGRESSION WITH MULTI-MODAL BRAIN IMAGING AND CLINICAL DATA. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2024 [Cited : ]; 10(2) : 2219-2224. Available from: https://ijariie.com/AdminUploadPdf/EARLY_DETECTION_OF_ALZHEIMER’S_DISEASE_PROGRESSION_WITH_MULTI_MODAL_BRAIN_IMAGING_AND_CLINICAL_DATA_ijariie23047.pdf
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