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Convolutional neural networks for classification of Alzheimer's disease: Overview and reproducible evaluation
Wen J, Thibeau-Sutre E, Diaz-Melo M, Samper-González J, Routier A, Bottani S, Dormont D, Durrleman S et al.. Medical image analysis, 2020-05-01
Topic: Brain imaging, connectivity and assessment
Moreover, we found that more than half of the surveyed papers may have suffered from data leakage and thus reported biased performance. Overall, the different 3D approaches (3D-subject, 3D-ROI, 3D-patch) achieved similar performances while that of the 2D slice approach was lower.
Key findings
- Moreover, we found that more than half of the surveyed papers may have suffered from data leakage and thus reported biased performance.
- Overall, the different 3D approaches (3D-subject, 3D-ROI, 3D-patch) achieved similar performances while that of the 2D slice approach was lower.
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Study details
- Evidence strengthLow
How this study scored 59/100
Published in a peer-reviewed journal, and it is a systematic review of all the studies on the question. Scored zero for sample size, effect reported and studied in people because the record does not state it. We have no data on journal's citation record, times cited, citations per year, impact for its field and year, cited by studies here, still being cited, senior author's track record, institution's track record and multi-centre collaboration, so those were left out: it earned 34 of the 58 points we could judge it on, which is 59 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Medical image analysis) |
| Journal's citation record | — / 4 | No journal record from OpenAlex — left out of this score |
| Study design | 12 / 12 | A systematic review of all the studies on the question (from PubMed type “Systematic Review”) |
| 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 | 2 / 5 | 2020 — within 10 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | A review of other studies — randomisation is not credited here |
| Times cited | — / 7 | No citation count (not found in OpenAlex) — left out of this score |
| Citations per year | — / 5 | No citation count or no year — left out of this score |
| Impact for its field and year | — / 6 | No field-weighted citation impact (OpenAlex has none yet) — left out of this score |
| Cited by studies here | — / 6 | Not yet checked against this library's citation graph — left out of this score |
| Still being cited | — / 4 | No yearly citation counts — left out of this score |
| Senior author's track record | — / 4 | Senior author's record not available — left out of this score |
| Institution's track record | — / 3 | No institution listed in OpenAlex — left out of this score |
| Multi-centre collaboration | — / 3 | Institutions not listed — left out of this score |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 32417716) |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Points | 34 / 58 | Scored on 11 of 20 parts. We have no data for the rest, so they are left out: 34 of the 58 points we could judge it on is 59 out of 100. |
| Total | 59 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
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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. The record's author list ends in “et al.”, so not every author is named. Check the citation against the original before you use it.
APA 7th
Wen, J., Thibeau-Sutre, E., Diaz-Melo, M., Samper-González, J., Routier, A., Bottani, S., et al. (2020). Convolutional neural networks for classification of Alzheimer's disease: Overview and reproducible evaluation. Medical image analysis. https://doi.org/10.1016/j.media.2020.101694
Vancouver
Wen J, Thibeau-Sutre E, Diaz-Melo M, Samper-González J, Routier A, Bottani S, et al. Convolutional neural networks for classification of Alzheimer's disease: Overview and reproducible evaluation. Medical image analysis. 2020. doi:10.1016/j.media.2020.101694. PMID: 32417716.
BibTeX
@article{wen2020-32417716,
author = {Wen, J. and Thibeau-Sutre, E. and Diaz-Melo, M. and Samper-González, J. and Routier, A. and Bottani, S. and Dormont, D. and Durrleman, S. and others},
title = {{Convolutional neural networks for classification of Alzheimer's disease: Overview and reproducible evaluation}},
journal = {Medical image analysis},
year = {2020},
doi = {10.1016/j.media.2020.101694},
pmid = {32417716},
url = {https://doi.org/10.1016/j.media.2020.101694}
}
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