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A multilayer multimodal detection and prediction model based on explainable artificial intelligence for Alzheimer's disease
El-Sappagh S, Alonso JM, Islam SMR, Sultan AM, Kwak KS.. Scientific reports, 2021-01-29
Topic: Amyloid, tau and blood-test diagnosis
As a result, physicians struggle to interpret these models, and feel it is hard to trust them.
Key findings
- As a result, physicians struggle to interpret these models, and feel it is hard to trust them.
Why it matters
The text only notes that physicians struggle to interpret these models and find it hard to trust them. No information is given about whether the model improves diagnosis, treatment, or prevention of Alzheimer's disease.
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Study details
- Participants1,048
- Effect size93.95%; 93.94%; 87.08%
- Evidence strengthLow
How this study scored 76/100
Published in a peer-reviewed journal, and it is a randomised controlled trial.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Scientific reports) |
| Journal's citation record | 3 / 4 | Scientific Reports: journal h-index 463 (OpenAlex, 2026-10-29) |
| Study design | 11 / 12 | A randomised controlled trial (from PubMed type “Randomized Controlled Trial”) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 3 / 5 | 2021 — within 6 year(s) of the newest study here |
| Sample size | 3 / 4 | 1,048 participants |
| Effect reported | 2 / 3 | Effect reported as a number, without an interval or test |
| Studied in people | 3 / 3 | Studied in people (participant count stated) |
| Randomised / blinded | 1 / 2 | Randomised (as stated in the record) |
| Times cited | 6 / 7 | Cited 356 times (OpenAlex, 2026-10-10) |
| Citations per year | 5 / 5 | 50.9 citations a year over 7 year(s) since 2021 |
| Impact for its field and year | 5 / 6 | Cited 32.5× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 3 / 6 | Cited by 11 other studies in this library |
| Still being cited | 4 / 4 | Cited 231 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 3 / 4 | Last-listed author Kyung Sup Kwak: h-index 50 (OpenAlex, whole career) |
| Institution's track record | 0 / 3 | Universidade de Santiago de Compostela: institution h-index 571 (OpenAlex) |
| Multi-centre collaboration | 2 / 3 | OpenAlex lists 5 institution(s) in 3 countries |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 33514817) |
| Free to read | 2 / 2 | Free to read |
| Total | 76 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
- DOI: 10.1038/s41598-021-82098-3
- PubMed: 33514817
- Original source →
- Free full text: Scientific Reports →
Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. Check the citation against the original before you use it.
APA 7th
El-Sappagh, S., Alonso, J. M., Islam, S. M. R., Sultan, A. M., & Kwak, K. S. (2021). A multilayer multimodal detection and prediction model based on explainable artificial intelligence for Alzheimer's disease. Scientific reports. https://doi.org/10.1038/s41598-021-82098-3
Vancouver
El-Sappagh S, Alonso JM, Islam SMR, Sultan AM, Kwak KS. A multilayer multimodal detection and prediction model based on explainable artificial intelligence for Alzheimer's disease. Scientific reports. 2021. doi:10.1038/s41598-021-82098-3. PMID: 33514817.
BibTeX
@article{elsappagh2021-33514817,
author = {El-Sappagh, S. and Alonso, J. M. and Islam, S. M. R. and Sultan, A. M. and Kwak, K. S.},
title = {{A multilayer multimodal detection and prediction model based on explainable artificial intelligence for Alzheimer's disease}},
journal = {Scientific reports},
year = {2021},
doi = {10.1038/s41598-021-82098-3},
pmid = {33514817},
url = {https://doi.org/10.1038/s41598-021-82098-3}
}
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