Evidence map›Paper›PMID 42389671›Full record

SynthesisFrontiers in dementia2026

Leveraging artificial intelligence for analysis of the gut microbiome for dementia diagnosis: a scoping review and discussion.

Laya Krishnan, Gaurie Gunasekaran, Tamanna Dhore, Alexa Lauinger, Vijaya Kolachalama, Suguna Pappu

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in dementia, 2026. 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

6 authors.

Laya KrishnanCarle Illinois College of Medicine, Urbana, IL, United States.
Gaurie GunasekaranCarle Illinois College of Medicine, Urbana, IL, United States.
Tamanna DhoreCarle Illinois College of Medicine, Urbana, IL, United States.
Alexa LauingerCarle Illinois College of Medicine, Urbana, IL, United States.
Vijaya KolachalamaBoston University School of Medicine, Boston, MA, United States.
Suguna PappuCarle Illinois College of Medicine, Urbana, IL, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Dementia, a multifactorial disease with progressive cognitive decline, has been linked to imbalances in the gut-brain axis. Emerging artificial intelligence tools have augmented the identification of several gastrointestinal biomarkers for differential dementia detection and severity, but current literature lacks a comprehensive review. Aims: This study aims to better quantify the applications of AI in the exploration of the gut microbiome for diagnosis of specific subtypes of dementia. Methods: Primary articles ( Results: Several studies utilized predictive models including random forests and neural networks to demonstrate alterations in the gut microbiota of Alzheimer's disease, an increasingly prevalent dementia subtype. These individuals have notably reduced levels of butyrate-producing bacteria, such as Conclusion: Distinct gut microbial compositions are associated with dementia. Furthermore, elucidating gut-brain interactions and their neurodegenerative implications can identify targets for earlier, synergistic diagnostics. Systematic review registration: https://osf.io/yw2dc/overview.

Indexed as

Alzheimer diseaseartificial intelligencebrain-gut axisdementiagastrointestinal microbiomemachine learning

Identifiers

PMID42389671
PMCPMC13318868

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Registered trials

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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.