Enhancing Alzheimer’s Disease Diagnosis Through Deep Learning-Leveraging VGG-16 Architecture and Adaptive Boosting-Reference-Cited by-同舟云学术

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Enhancing Alzheimer’s Disease Diagnosis Through Deep Learning-Leveraging VGG-16 Architecture and Adaptive Boosting

Published:2024-07-03 Issue: Volume:58 Page:457-464
ISSN:
Container-title:2024 5th International Conference on Image Processing and Capsule Networks (ICIPCN)
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Author:

Irrigisetty Harshavelu¹,Madhavi K. Reddy²,Avanija J.³,Thokala Rishi Reddy⁴,Varma K S S Rishi⁴

Affiliation:

1. Sree Vidyanikethan Engineering College,Department of CSE,Tirupati,India

2. Mohan Babu University(Erstwhile Sree Vidyanikethan Engineering College),Department of AI&ML,Tirupati,India

3. Mohan Babu University(Erstwhile Sree Vidyanikethan Engineering College),School of Computing,Tirupati,India

4. SRM Institute of Science and Technology,Department of CSE,Chennai,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10660666/10660641/10661068.pdf?arnumber=10661068

Reference15 articles.

1. Alzheimer’s Disease;Fight Dementia Australia. (n.d.)

2. Generalizable deep learning model for early Alzheimer’s disease detection from structural MRIs

3. Corpus Callosum Radiomics-Based Classification Model in Alzheimer's Disease: A Case-Control Study

4. Early prediction of Alzheimer’s disease using convolutional neural network: a review;Patil;Egypt J Neurol Psychiatry Neurosurg,2022

5. Multimodal deep learning models for early detection of Alzheimer’s disease stage

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