Abuhmed T, El-Sappagh S, Alonso JM (2021) Robust hybrid deep learning models for Alzheimer’s progression detection. Knowl-Based Syst 213:106688

Article  Google Scholar 

Abunadi I (2022) Deep and hybrid learning of MRI diagnosis for early detection of the progression stages in Alzheimer’s disease. Connect Sci 34(1):2395–2430

Article  Google Scholar 

Alatrany A, Hussain A, Mustafina J, Al-Jumeily D (2021) A novel hybrid machine learning approach using deep learning for the prediction of alzheimer disease using genome data. Intelligent computing theories and application: 17th International Conference, ICIC 2021, Shenzhen, China, August 12–15, 2021, Proceedings, Part III 17. Springer International Publishing, NY, pp 253–266

Chapter  Google Scholar 

AlSaeed D, Omar SF (2022) Brain MRI analysis for Alzheimer’s disease diagnosis using CNN-based feature extraction and machine learning. Sensors 22(8):2911

Article  PubMed  PubMed Central  Google Scholar 

Azam Zia M, Saeed Z, Asghar N, Majeed B, Hashim M (2022) Identification of Alzheimer disease by using hybrid deep models. International Conference on Management Science and Engineering Management. Springer International Publishing, Cham, pp 465–475

Google Scholar 

Balaji P, Chaurasia MA, Bilfaqih SM, Muniasamy A, Alsid LEG (2023) Hybridized deep learning approach for detecting Alzheimer’s disease. Biomedicines 11(1):149

Article  PubMed  PubMed Central  Google Scholar 

Battineni G, Chintalapudi N, Amenta F, Traini E (2021) Deep learning type convolution neural network architecture for multiclass classification of Alzheimer’s disease. Bioimaging 2:209–215

Google Scholar 

Fareed MMS, Zikria S, Ahmed G, Mahmood S, Aslam M, Jillani SF, Moustafa A, Asad M (2022) Add-net: an effective deep learning model for early detection of Alzheimer disease in MRI scans. IEEE Access 10:96930–96951

Article  Google Scholar 

Goenka N, Tiwari S (2022) AlzVNet: a volumetric convolutional neural network for multiclass classification of Alzheimer’s disease through multiple neuroimaging computational approaches. Biomed Signal Process Control 74:103500

Article  Google Scholar 

Kumar MS, Azath H, Velmurugan AK, Padmanaban K, Subbiah M (2023) Prediction of Alzheimer’s disease using hybrid machine learning technique. AIP Conference Proceedings. AIP Publishing, Melville

Google Scholar 

Leela M, Helenprabha K, Sharmila L (2023) Prediction and classification of Alzheimer disease categories using integrated deep transfer learning approach. Meas Sens 27:100749

Article  Google Scholar 

Lu SY, Zhang YD, Yao YD (2025) A regularized transformer with adaptive token fusion for Alzheimer’s disease diagnosis in brain magnetic resonance images. Eng Appl Artif Intell 155:111058

Article  Google Scholar 

Mahendran N, Vincent PDR, Srinivasan K, Chang CY (2021) Improving the classification of Alzheimer’s disease using hybrid gene selection pipeline and deep learning. Front Genet 12:784814

Article  PubMed  PubMed Central  Google Scholar 

Matlani P (2024) BiLSTM-ANN: early diagnosis of Alzheimer’s disease using hybrid deep learning algorithms. Multimed Tools Appl 83(21):60761–60788

Article  Google Scholar 

Mohammad F, Al Ahmadi S (2023) Alzheimer’s disease prediction using deep feature extraction and optimization. Mathematics 11(17):3712

Article  Google Scholar 

Mohammed BA, Senan EM, Rassem TH, Makbol NM, Alanazi AA, Al-Mekhlafi ZG, Almurayziq TS, Ghaleb FA (2021) Multi-method analysis of medical records and MRI images for early diagnosis of dementia and Alzheimer’s disease based on deep learning and hybrid methods. Electronics 10(22):2860

Article  Google Scholar 

Nagarathna, C. R., & Kusuma, M. (2021). Comparative study of detection and classification of Alzheimer's disease using Hybrid model and CNN. In: 2021 International Conference on Disruptive Technologies for Multi-Disciplinary Research and Applications (CENTCON) (Vol. 1, pp. 43–46). IEEE.

Nawaz H, Maqsood M, Afzal S, Aadil F, Mehmood I, Rho S (2021) A deep feature-based real-time system for Alzheimer disease stage detection. Multimedia Tools Appl 80:35789–35807

Article  Google Scholar 

Nour M, Senturk U, Polat K (2024) A novel hybrid model in the diagnosis and classification of Alzheimer’s disease using EEG signals: deep ensemble learning (DEL) approach. Biomed Signal Process Control 89:105751

Article  Google Scholar 

Papadaki E, Exarchos T, Vlamos P, Vrahatis A (2022) A hybrid deep learning model for predicting the early Alzheimer’s disease stages using MRI. Proc Hellenic Conf Artif Intell 38:1–6

Google Scholar 

Raghavaiah P, Varadarajan S (2022) A CAD system design for Alzheimer’s disease diagnosis using temporally consistent clustering and hybrid deep learning models. Biomed Signal Process Control 75:103571

Article  Google Scholar 

Shamrat FJM, Akter S, Azam S, Karim A, Ghosh P, Tasnim Z, Hasib KM, De Boer F, Ahmed K (2023) AlzheimerNet: an effective deep learning based proposition for alzheimer’s disease stages classification from functional brain changes in magnetic resonance images. IEEE Access 11:16376–16395

Article  Google Scholar 

Tanveer M, Rashid AH, Ganaie MA, Reza M, Razzak I, Hua KL (2021) Classification of Alzheimer’s disease using ensemble of deep neural networks trained through transfer learning. IEEE J Biomed Health Inform 26(4):1453–1463

Article  Google Scholar 

Jack CR Jr, Bernstein MA, Fox NC, Thompson P, Alexander G, Harvey D, et al (2008) The Alzheimer’s Disease Neuroimaging Initiative (ADNI): MRI methods. J Magnet Res Imag 27(4):685–691. https://doi.org/10.1002/jmri.21049

Vidhya R, Banavath D, Kayalvili S, Naidu SM, Prabu VC, Sugumar D, Vidhya RG (2023) Alzheimer’s disease detection using residual neural network with LSTM hybrid deep learning models. J Intell Fuzzy Syst 45:12095

Google Scholar 

Wang S, Zhou T, Shen Y, Li Y, Huang G, Hu Y (2025) Generative AI enables EEG super-resolution via spatio-temporal adaptive diffusion learning. IEEE Trans Consum Electron. https://doi.org/10.1109/TCE.2025.3528438

Article  Google Scholar 

Zong Y, Zuo Q, Ng MKP, Lei B, Wang S (2024) A new brain network construction paradigm for brain disorder via diffusion-based graph contrastive learning. IEEE Trans Pattern Anal Mach Intell. https://doi.org/10.1109/TPAMI.2024.3442811

Article  PubMed  Google Scholar