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Hippocampal shape analysis of Alzheimer disease based on machine learning methods
Li S, Shi F, Pu F, Li X, Jiang T, Xie S, Wang Y.. AJNR. American journal of neuroradiology, 2007-08-01
Topic: Amyloid, tau and blood-test diagnosis
Background and purpose Alzheimer disease (AD) is a neurodegenerative disease characterized by progressive dementia. The hippocampus is particularly vulnerable to damage at the very earliest stages of AD. This article seeks to evaluate critical AD-associated regional changes in the hippocampus using machine learning methods. Materials and methods High-resolution MR images were acquired from 19 patients with AD and 20 age- and sex-matched healthy control subjects. Regional changes of bilateral hippocampi were characterized using computational anatomic mapping methods. A feature selection method for support vector machine and leave-1-out cross-validation was introduced to determine regional shape differences that minimized the error rate in the datasets. Results Patients with AD showed significant deformations in the CA1 region of bilateral hippocampi, as well as the subiculum of the left hippocampus. There were also some changes in the CA2-4 subregions of the left hippocampus among patients with AD. Moreover, the left hippocampal surface showed greater variations than the right compared with those in healthy control subjects. The accuracies of leave-1-out cross-validation and 3-fold cross-validation experiments for assessing the reliability of these subregions were more than 80% in bilateral hippocampi. Conclusion Subtle and spatially complex deformation patterns of hippocampus between patients with AD and healthy control subjects can be detected by machine learning methods.
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
APA 7th
Li, S., Shi, F., Pu, F., Li, X., Jiang, T., Xie, S., et al. (2007). Hippocampal shape analysis of Alzheimer disease based on machine learning methods. AJNR. American journal of neuroradiology. https://doi.org/10.3174/ajnr.a0620
Vancouver
Li S, Shi F, Pu F, Li X, Jiang T, Xie S, et al. Hippocampal shape analysis of Alzheimer disease based on machine learning methods. AJNR. American journal of neuroradiology. 2007. doi:10.3174/ajnr.a0620. PMID: 17698538.
BibTeX
@article{li2007-17698538,
author = {Li, S. and Shi, F. and Pu, F. and Li, X. and Jiang, T. and Xie, S. and Wang, Y.},
title = {{Hippocampal shape analysis of Alzheimer disease based on machine learning methods}},
journal = {AJNR. American journal of neuroradiology},
year = {2007},
doi = {10.3174/ajnr.a0620},
pmid = {17698538},
url = {https://doi.org/10.3174/ajnr.a0620}
}
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 names 7 authors; APA and Vancouver show the first six, BibTeX and the downloads carry all of them. Check the citation against the original before you use it.
Key findings
- Results Patients with AD showed significant deformations in the CA1 region of bilateral hippocampi, as well as the subiculum of the left hippocampus.
- Moreover, the left hippocampal surface showed greater variations than the right compared with those in healthy control subjects.
Why it matters
This small study of 19 Alzheimer's patients and 20 controls found specific shape changes in the hippocampus, especially the CA1 region, using machine learning. It is a structural imaging study and does not test any treatment, cure, or prevention.
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Study details
- Participants19
- Evidence strengthLow
How this study scored 46/100
Published in a peer-reviewed journal. Scored zero for study design, effect reported and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (AJNR. American journal of neuroradiology) |
| Journal's citation record | 2 / 4 | American Journal of Neuroradiology: journal h-index 182 (OpenAlex, 2026-10-29) |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| 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 | 1 / 5 | 2007 — within 20 year(s) of the newest study here |
| Sample size | 1 / 4 | 19 participants |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 3 / 3 | Studied in people (participant count stated) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 5 / 7 | Cited 126 times (OpenAlex, 2026-10-10) |
| Citations per year | 2 / 5 | 6.0 citations a year over 21 year(s) since 2007 |
| Impact for its field and year | 3 / 6 | Cited 3.5× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 2 / 6 | Cited by 7 other studies in this library |
| Still being cited | 1 / 4 | Cited 7 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 2 / 4 | Last-listed author Yinghui Wang: h-index 28 (OpenAlex, whole career) |
| Institution's track record | 2 / 3 | Chinese Academy of Sciences: institution h-index 1,801 (OpenAlex) |
| Multi-centre collaboration | 2 / 3 | OpenAlex lists 5 institution(s) in 1 country |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 17698538) |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Total | 46 / 100 | — |
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Read the original
- DOI: 10.3174/ajnr.a0620
- PubMed: 17698538
- Original source →
- Free full text: American Journal of Neuroradiology →
Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).
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