Skip to content
2000
image of IoMT Requirements, Integrated Diagnosis, and Future Trends for Multimodal Early Detection of Alzheimer’s Disease

There is no abstract available.

Loading

Article metrics loading...

/content/journals/car/10.2174/0115672050393916250520101258
2025-05-21
2025-06-17
Loading full text...

Full text loading...

References

  1. Zhang Y. Mild cognitive impairment recognition via gene expression mining and neuroimaging techniques. Frontiers Media Lausanne 2022 10.3389/978‑2‑8325‑0840‑4
    [Google Scholar]
  2. Apathy associated with Alzheimer’s disease. Curr. Alzheimer Res. 2025 21 8 527 537 10.2174/0115672050350970241216072400 39716787
    [Google Scholar]
  3. Capgras syndrome in dementia: A systematic review of case studies. Curr. Alzheimer Res. 2024 21 5 312 323 10.2174/0115672050335918240919073012 39411962
    [Google Scholar]
  4. 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. 2024 2024 10.26599/TST.2024.9010080
    [Google Scholar]
  5. EEG signal-based machine learning approaches for Alzheimer’s disease: A review of methodological analysis. EICEEAI 2023 Dec 1 6 10.1109/EICEEAI60672.2023.10590088
    [Google Scholar]
  6. A novel EEG-based deep approach for diagnosing Alzheimer’s disease using attention-time-aware LSTM. EICEEAI 2023 Dec 1 6 10.1109/EICEEAI60672.2023.10590201
    [Google Scholar]
  7. Fusing convolutional learning and attention-based Bi-LSTM networks for early Alzheimer’s diagnosis from EEG signals towards IoMT. Sci. Rep. 2024 14 1 26002 10.1038/s41598‑024‑77876‑8 39472526
    [Google Scholar]
  8. Using entropy as the convergence criteria of ant colony optimization and the application at gene chip data analysis. Curr. Alzheimer Res. 2024 21 5 324 341 10.2174/0115672050325388240823092338 39279692
    [Google Scholar]
  9. Transforming Alzheimer’s digital caregiving through large language models. Curr. Alzheimer Res. 2024 21 7 503 516 10.2174/0115672050301740241118044604 39592896
    [Google Scholar]
  10. hdWGCNA and cellular communication identify active nk cell subtypes in Alzheimer’s disease and screen for diagnostic markers through machine learning. Curr. Alzheimer Res. 2024 21 2 120 140 10.2174/0115672050314171240527064514 38808722
    [Google Scholar]
/content/journals/car/10.2174/0115672050393916250520101258
Loading
/content/journals/car/10.2174/0115672050393916250520101258
Loading

Data & Media loading...


  • Article Type:
    Editorial
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test