Articlenpj aging2025
Deep learning of conversation-based 'filmstrips' for robust Alzheimer's disease detection.
Article in npj aging, 2025. 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
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Early detection of Alzheimer's disease remains complex and costly despite advancements in neurobiological markers. We propose an innovative approach based on the topological and kinetic analysis of verbal exchanges to distinguish patients from healthy individuals. Without requiring full transcription, we leverage a convolutional network capable of identifying discursive patterns indicative of cognitive impairments. Our experiments, conducted with 80 participants, demonstrate performance levels exceeding 95% in cross-validation, comparable to computational approaches relying on biological markers. This robust and minimally invasive methodology could be easily integrated into clinical protocols, enhancing current diagnostics. It also holds the promise of cost-effectively extending monitoring to other neurodegenerative or psychiatric diseases.
Identifiers
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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.