Evidence map›Paper›PMID 42490971›Full record

ArticleAlzheimer's & dementia (New York, N. Y.)

Agentic neurotechnology: A multi-agent AI framework for next-generation dementia care.

Kevin Mekulu, Faisal Aqlan, Hui Yang

Abstract read
In one paragraph

Article in Alzheimer's & dementia (New York, N. Y.). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Kevin MekuluComplex Systems Monitoring Modeling and Control Laboratory Pennsylvania State University University Park Pennsylvania USA.ORCID https://orcid.org/0009-0004-8584-6693
Faisal AqlanCenter for Human Systems Engineering University of Louisville Louisville Kentucky USA.
Hui YangComplex Systems Monitoring Modeling and Control Laboratory Pennsylvania State University University Park Pennsylvania USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dementia care is reaching a technological turning point as rapid advances in artificial intelligence (AI), digital biomarkers, and sensor-based monitoring continue to outpace current clinical practice. Yet most tools remain episodic and disconnected from the everyday environments where cognitive change unfolds. Early cognitive drift often goes unnoticed, the mild cognitive impairment (MCI) window remains a major diagnostic gap, and care teams lack continuous, actionable insights. In this perspective, we introduce Agentic Neurotechnology, an integrated framework that combines adaptive multi-agent AI systems with longitudinal cognitive modeling to support proactive and individualized dementia care. We define a five-layer agentic stack consisting of (1) sensing and digital biomarker agents, (2) interpretation and reasoning agents, (3) longitudinal cognitive trajectory models, (4) care navigation agents, and (5) population-level forecasting agents. We further outline the Cognitive Continuum Loop, a closed-cycle process in which detection, interpretation, reasoning, monitoring, intervention, and adaptation occur continuously across the care environment. This framework highlights three actionable windows for cognitive intervention: the Preclinical Risk Detection window, the MCI Detection window, and the Functional Instability Response window. Each stage presents unique opportunities for agentic AI systems that operate continuously rather than through isolated assessments. We conclude by presenting a translational pathway for deploying agentic neurotechnologies across assisted living, primary care, telehealth, and home-based settings. The goal is to enable earlier detection, greater clinical efficiency, and more personalized cognitive support. Agentic Neurotechnology reframes AI not as a passive screening tool but as an active partner in continuous cognitive care.

Indexed as

Agentic AIcognitive screeningdementia caredigital biomarkerslongitudinal modelingmulti‐agent systems

Identifiers

PMID42490971
PMCPMC13375936

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.