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

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).