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40/100

✓ Peer-reviewed alzhub usefulness score 40 out of 100. Getting a diagnosis

Topic: Amyloid, tau and blood-test diagnosis

Plain-language summary

As the U.S. population ages, Alzheimer's disease and related dementias (ADRD) cases are increasing, resulting in long wait times for specialist care. We review state-of-the-art artificial intelligence (AI) applications in ADRD care, from streamlining clinical diagnosis to pioneering novel digital biomarkers. Near-term AI applications include neuroimaging interpretation, conversational agents for patient interviews, and digital cognitive assessments. Large language models show promise as collaborative partners, helping clinicians interpret complex data while supporting patients and caregivers. Emerging digital biomarkers-speech analysis, passive monitoring through wearable devices, electronic health record analysis, and multiomics-offer potential for continuous monitoring to detect cognitive decline years before traditional assessments. Despite the acceleration of AI innovation, most of these systems are inaccessible in clinical practice. Implementation bottlenecks include limited external validation, technical challenges, model biases, infrastructure, and regulatory requirements. This review aims to help neurologists navigate this rapidly evolving AI landscape and prepare for implementation in ADRD care.

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APA 7th

Breithaupt, A. G., Tang, A., Paolillo, E. W., Bibars, M., Johnson, E. C. B., Saloner, R., et al. (2025). Review of Artificial Intelligence for Clinical Use in Alzheimer's Disease and Related Dementias. Seminars in Neurology. https://doi.org/10.1055/a-2744-9871

Vancouver

Breithaupt AG, Tang A, Paolillo EW, Bibars M, Johnson ECB, Saloner R, et al. Review of Artificial Intelligence for Clinical Use in Alzheimer's Disease and Related Dementias. Seminars in Neurology. 2025. doi:10.1055/a-2744-9871. PMID: 41314410.

BibTeX

@article{breithaupt2025-41314410,
  author  = {Breithaupt, Andrew G. and Tang, Alice and Paolillo, Emily W. and Bibars, Merna and Johnson, Erik C. B. and Saloner, Rowan and Possin, Katherine L. and Windon, Charles and others},
  title   = {{Review of Artificial Intelligence for Clinical Use in Alzheimer's Disease and Related Dementias}},
  journal = {Seminars in Neurology},
  year    = {2025},
  doi     = {10.1055/a-2744-9871},
  pmid    = {41314410},
  url     = {https://doi.org/10.1055/a-2744-9871}
}

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How to read this study

Design: our record does not state a study design, so check the methods section of the original before weighing the result.
Size: the record gives no participant count. Look for one in the original before trusting a pattern.
Effect: the record gives no effect size, so the summary above cannot say how large any difference was.

What the evidence grade means here

This page is graded low. alzhub.org assigns the grade automatically from keywords in the abstract, not from reading the paper. Low means the abstract matched neither pattern. It is the default label, and it does not mean the work is poor; many sound lab and imaging papers land here. It can add at most 5 of the 100 points in the study score, and it is a label about design, not a verdict on whether the findings are true.

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Key findings

Large language models show promise as collaborative partners, helping clinicians interpret complex data while supporting patients and caregivers.
Emerging digital biomarkers-speech analysis, passive monitoring through wearable devices, electronic health record analysis, and multiomics-offer potential for continuous monitoring to detect cognitive decline years before traditional assessments.
Despite the acceleration of AI innovation, most of these systems are inaccessible in clinical practice.
Implementation bottlenecks include limited external validation, technical challenges, model biases, infrastructure, and regulatory requirements.
This review aims to help neurologists navigate this rapidly evolving AI landscape and prepare for implementation in ADRD care.

Why it matters

This review describes artificial intelligence applications in Alzheimer's disease and related dementias care, including neuroimaging interpretation, digital cognitive assessments, and emerging digital biomarkers. It notes that most of these systems are not yet accessible in clinical practice and does not itself treat, cure or prevent Alzheimer's disease.

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Study details

Evidence strengthLow

How this study scored 40/100

Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported, studied in people and randomized / blinded because the record does not state it.

Component	Points	Why
Journal tier	7 / 10	Tier 3 — peer-reviewed journal (Seminars in Neurology)
Journal's citation record	1 / 4	Seminars in Neurology: journal h-index 106 (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	4 / 5	2025 — within 3 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)
Randomized / blinded	0 / 2	No randomization or blinding stated — scores zero (not stated in the record — scored 0)
Times cited	2 / 7	Cited 6 times (OpenAlex, 2026-10-10)
Citations per year	1 / 5	2.0 citations a year over 3 year(s) since 2025
Impact for its field and year	3 / 6	Cited 3.8× the average for papers of its field and year (OpenAlex FWCI)
Cited by studies here	0 / 6	No other study in this library cites it
Still being cited	1 / 4	Cited 6 times in 2024–2026 (2026 still in progress; OpenAlex)
Senior author's track record	2 / 4	Last-listed author Pedro Pinheiro‐Chagas: h-index 20 (OpenAlex, whole career)
Institution's track record	2 / 3	University of California, Berkeley: institution h-index 2,012 (OpenAlex)
Multicenter collaboration	2 / 3	OpenAlex lists 6 institution(s) in 1 country
Indexed in PubMed	2 / 2	Indexed in PubMed (PMID 41314410)
Free to read	2 / 2	Free to read
Total	40 / 100	—

What each of these 20 components measures, and what this score is not →

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