Corrigendum to: Advancing Alzheimer's Disease Diagnosis Using VGG19 and XGBoost: A Neuroimaging-Based Method.

Abstract

The publisher identified that references 42 and 43 were duplicated in the published version of this article [1]. The error has now been corrected. The original article can be found online at: https://www.benthamscience.com/article/150567 Details of the error and the correction are provided below: Original: [42] Muksimova S, Umirzakova S, Iskhakova N, Khaitov A, Cho YI. Advanced convolutional neural network with attention mechanism for Alzheimer's disease classification using MRI. Comput Biol Med 2025; 190, 110095. [43] Muksimova S, Umirzakova S, Iskhakova N, Khaitov A, Cho YI. Advanced convolutional neural network with attention mechanism for Alzheimer's disease classification using MRI. Comput Biol Med 2025; 190: 110095. http://dx.doi.org/10.1016/j.compbiomed.2025.110095 PMID: 40158456 Corrected: [42] Muksimova S, Umirzakova S, Iskhakova N, Khaitov A, Cho YI. Advanced convolutional neural network with attention mechanism for Alzheimer's disease classification using MRI. Comput Biol Med 2025; 190, 110095. http://dx.doi.org/10.1016/j.compbiomed.2025.110095 PMID: 40158456 [43] Olaimat MA, Bozdag S, Saeed F. TA-RNN: An attention-based time-aware recurrent neural network architecture to predict progression of Alzheimer's disease. Alzheimer's Dement 2024; 20(S1).