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Modeling disease progression via multi-task learning
Zhou J, Liu J, Narayan VA, Ye J, Alzheimer's Disease Neuroimaging Initiative.. NeuroImage, 2013-04-12
Topic: Risk, prevention and care in population studies
Alzheimer's disease (AD), the most common type of dementia, is a severe neurodegenerative disorder. Identifying biomarkers that can track the progress of the disease has recently received increasing attentions in AD research. An accurate prediction of disease progression would facilitate optimal decision-making for clinicians and patients.
Key findings
- Identifying biomarkers that can track the progress of the disease has recently received increasing attentions in AD research.
- An accurate prediction of disease progression would facilitate optimal decision-making for clinicians and patients.
- A definitive diagnosis of AD requires autopsy confirmation, thus many clinical/cognitive measures including Mini Mental State Examination (MMSE) and Alzheimer's Disease Assessment Scale cognitive subscale (ADAS-Cog) have been designed to evaluate the cognitive status of the patients and used as important criteria for clinical diagnosis of probable AD.
- In this paper, we consider the problem of predicting disease progression measured by the cognitive scores and selecting biomarkers predictive of the progression.
Why it matters
This study describes a computer method for modeling how Alzheimer's disease progresses over time. It does not test any treatment, cure, or prevention for the disease.
Study details
- Study designlongitudinal study
- Evidence strengthModerate
How this study scored 56/100
Published in a peer-reviewed journal, and it is a longitudinal study following the same people over time. Scored zero for sample size, effect reported, studied in people and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (NeuroImage) |
| Journal's citation record | 4 / 4 | NeuroImage: journal h-index 523 (OpenAlex, 2026-10-29) |
| Study design | 7 / 12 | A longitudinal study following the same people over time |
| Strength of evidence | 3 / 5 | Rated “moderate” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 1 / 5 | 2013 — within 20 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 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 5 / 7 | Cited 215 times (OpenAlex, 2026-10-10) |
| Citations per year | 3 / 5 | 14.3 citations a year over 15 year(s) since 2013 |
| Impact for its field and year | 4 / 6 | Cited 9.0× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 2 / 6 | Cited by 4 other studies in this library |
| Still being cited | 2 / 4 | Cited 36 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 4 / 4 | Last-listed author Jieping Ye: h-index 105 (OpenAlex, whole career) |
| Institution's track record | 1 / 3 | Arizona State University: institution h-index 987 (OpenAlex) |
| Multi-centre collaboration | 1 / 3 | OpenAlex lists 2 institution(s) in 1 country |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 23583359) |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Total | 56 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
May need a subscription OpenAlex found no free copy of the full text (checked 6 Feb 1020), so the publisher may charge for it. The PubMed abstract is free.
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
Zhou, J., Liu, J., Narayan, V. A., Ye, J., & Alzheimer's Disease Neuroimaging Initiative. (2013). Modeling disease progression via multi-task learning. NeuroImage. https://doi.org/10.1016/j.neuroimage.2013.03.073
Vancouver
Zhou J, Liu J, Narayan VA, Ye J, Alzheimer's Disease Neuroimaging Initiative. Modeling disease progression via multi-task learning. NeuroImage. 2013. doi:10.1016/j.neuroimage.2013.03.073. PMID: 23583359.
BibTeX
@article{zhou2013-23583359,
author = {Zhou, J. and Liu, J. and Narayan, V. A. and Ye, J. and {Alzheimer's Disease Neuroimaging Initiative}},
title = {{Modeling disease progression via multi-task learning}},
journal = {NeuroImage},
year = {2013},
doi = {10.1016/j.neuroimage.2013.03.073},
pmid = {23583359},
url = {https://doi.org/10.1016/j.neuroimage.2013.03.073}
}
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4 studies in the alzhub library list this one in their references.