ReviewDigital health
Bridging the islands of innovation: A machine-assisted Semantic-Bibliometric review and conceptual roadmap for closed-loop digital dementia care.
Review in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Artificial intelligence (AI), extended reality (XR), and socially assistive robotics (SAR) are each advancing Alzheimer's disease (AD) research and care at a rapid pace. Yet despite substantial progress within each domain, clinical implementation remains weakly integrated across diagnostic, therapeutic, and care functions, producing islands of innovation rather than coordinated care systems. Methods: We conducted a machine-assisted semantic-bibliometric synthesis of 2,636 publications on AI-, immersive technology/VR-, and SAR-enabled approaches to AD diagnosis, intervention, and care published between 2021 and 2025. Available title-abstract metadata were encoded using SBERT embeddings, projected via UMAP, and clustered using K-Means to characterize the functional topology of the field. From this mapped corpus, we selected a semantically central subset of 50 studies for high-fidelity full-text synthesis, preserving cross-domain representativeness while maintaining interpretive tractability. Results: The mapped landscape suggests a three-part pattern of architectural separation. Precision neuroimaging (Cluster C4, 22%) functions primarily as a state-oriented diagnostic domain. Immersive therapeutics (Cluster C2, 48%), the largest cluster, increasingly incorporate adaptive personalization but remain weakly connected to biomarker-based stratification. Embodied robotic care (Cluster C5, 10%) addresses behavioral stabilization with little longitudinal coupling to upstream sensing. Across all three domains, high component-level sophistication coexists with limited evidence of cross-layer coordination. Conclusion: Contemporary digital solutions for AD remain predominantly siloed and state-oriented rather than longitudinally integrated. We synthesize these observations into a conceptual Closed-Loop Architecture, proposed as a roadmap for future integrated digital dementia care. Advancing this agenda will depend on interoperable infrastructure, longitudinal modeling, and prospective cross-layer evaluation-not solely on further isolated gains in classification accuracy.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.