f IoMT Requirements, Integrated Diagnosis, and Future Trends for Multimodal Early Detection of Alzheimer’s Disease

References

1. ZhangY. YizhangJi. Sang-BingT. Mohammad, K. Mild cognitive impairment recognition via gene expression mining and neuroimaging techniques.LausanneFront. Media2022ISBN: 9782832508404.10.3389/978‑2‑8325‑0840‑4
   [Google Scholar]
2. WuD. BoZ. YajuanC. ShumingH. Apathy Associated with alzheimer’s disease.Curr. Alzheimer Res.202421852753710.2174/0115672050350970241216072400
   [Google Scholar]
3. MargaritiC. MirceaM-T. Capgras syndrome in dementia: a systematic review of case studies.Curr. Alzheimer Res.202421531232310.2174/0115672050335918240919073012
   [Google Scholar]
4. KhosraviM. HosseinP. KhosroR. Novel classification scheme for early Alzheimer’s disease (AD) severity diagnosis using deep features of the hybrid cascade attention architecture: Early detection of AD on MRI Scans.Tsinghua Sci. Technol.2025302572259110.26599/TST.2024.9010080
   [Google Scholar]
5. KhosraviM. HosseinP. MohammedA. KhosroR. EEG signal-based machine learning approaches for Alzheimer’s disease: a review of methodological analysis.EICEEAI202310.1109/EICEEAI60672.2023.10590088
   [Google Scholar]
6. KhosraviM. HosseinP. MohammedA. KhosroR. A novel EEG-based deep approach for diagnosing Alzheimer’s disease using attention-time-aware LSTM.EICEEAI202310.1109/EICEEAI60672.2023.10590201
   [Google Scholar]
7. KhosraviM. HosseinP. KhosroR. MohammadS.H. Fusing convolutional learning and attention-based Bi-LSTM networks for early Alzheimer’s diagnosis from EEG signals towards IoMT.Sci. Reports20241412600210.1038/s41598‑024‑77876‑8
   [Google Scholar]
8. GaoC. XinpingP. ChongbaoW. JingyueH. HuiL. ChengjiangZ. KunpeiJ. WeiqiL. PengtaoZ. ZihangZ. YanyuW. ChaoyangP. Using entropy as the convergence criteria of ant colony optimization and the application at gene chip data analysis.Curr. Alzheimer Res.202421532434110.2174/0115672050325388240823092338
   [Google Scholar]
9. KimS. DongY.H. JihyeB. Transforming Alzheimer’s digital caregiving through large language models.Curr. Alzheimer Res.202421750351610.2174/0115672050301740241118044604
   [Google Scholar]
10. SongG. HaoyangW. HaiqingC. ShengkeZ. QingwenH. HaotianL. ClaireF. GuanhuY. HaoC. hdWGCNA and cellular communication identify Active NK cell subtypes in Alzheimer’s disease and screen for diagnostic markers through machine learning.Curr. Alzheimer Res.202421212014010.2174/0115672050314171240527064514
    [Google Scholar]