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[Use AI for Dementia Diagnosis]
Shotai Kobayashi. Brain and nerve = Shinkei kenkyu no shinpo, 2019-07
Topic: Brain imaging, connectivity and assessment
Using AI for dementia diagnosis is still in research stage, however some of the work points to the development of new medical devices. One is a voxel-based morphometry analysis of brain atrophy, and a brain network analysis using a resting state functional MRI and diffusion tensor imaging. The other is an application to detect dementia in daily life using "IoT" technology. As it has been determined that elderly people's dementia is closely related to lifestyle, the use of AI in the diagnosis is to predict the possibility of dementia in the preclinical stage and to link it to prevention, rather than to provide a definitive diagnosis.
Key findings
- Using AI for dementia diagnosis is still in research stage, however some of the work points to the development of new medical devices.
- One is a voxel-based morphometry analysis of brain atrophy, and a brain network analysis using a resting state functional MRI and diffusion tensor imaging.
- The other is an application to detect dementia in daily life using "IoT" technology.
- As it has been determined that elderly people's dementia is closely related to lifestyle, the use of AI in the diagnosis is to predict the possibility of dementia in the preclinical stage and to link it to prevention, rather than to provide a definitive diagnosis.
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Study details
- Evidence strengthLow
How this study scored 39/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported, studied in people and randomised / blinded 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, multi-centre collaboration and free to read, so those were left out: it earned 22 of the 56 points we could judge it on, which is 39 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Brain and nerve = Shinkei kenkyu no shinpo) |
| Journal's citation record | — / 4 | No journal record from OpenAlex — left out of this score |
| 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 | 2 / 5 | 2019 — 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 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| 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 31289248) |
| Free to read | — / 2 | Access not recorded — left out of this score |
| Points | 22 / 56 | Scored on 10 of 20 parts. We have no data for the rest, so they are left out: 22 of the 56 points we could judge it on is 39 out of 100. |
| Total | 39 / 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. Check the citation against the original before you use it.
APA 7th
Kobayashi, S. (2019). [Use AI for Dementia Diagnosis]. Brain and nerve = Shinkei kenkyu no shinpo. https://doi.org/10.11477/mf.1416201346
Vancouver
Kobayashi S. [Use AI for Dementia Diagnosis]. Brain and nerve = Shinkei kenkyu no shinpo. 2019. doi:10.11477/mf.1416201346. PMID: 31289248.
BibTeX
@article{kobayashi2019-31289248,
author = {Kobayashi, Shotai},
title = {{[Use AI for Dementia Diagnosis]}},
journal = {Brain and nerve = Shinkei kenkyu no shinpo},
year = {2019},
doi = {10.11477/mf.1416201346},
pmid = {31289248},
url = {https://doi.org/10.11477/mf.1416201346}
}
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