Artificial intelligence-based personalized diet: A pilot clinical study for irritable bowel syndrome

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dc.contributor.authorKarakan T.
dc.contributor.authorGundogdu A.
dc.contributor.authorAlagözlü H.
dc.contributor.authorEkmen N.
dc.contributor.authorOzgul S.
dc.contributor.authorTunali V.
dc.contributor.authorHora M.
dc.contributor.authorBeyazgul D.
dc.contributor.authorNalbantoglu O.U.
dc.date.accessioned2024-07-22T08:05:02Z
dc.date.available2024-07-22T08:05:02Z
dc.date.issued2022
dc.description.abstractWe enrolled consecutive IBS-M patients (n = 25) according to Rome IV criteria. Fecal samples were obtained from all patients twice (pre-and post-intervention) and high-throughput 16S rRNA sequencing was performed. Six weeks of personalized nutrition diet (n = 14) for group 1 and a standard IBS diet (n = 11) for group 2 were followed. AI-based diet was designed based on optimizing a personalized nutritional strategy by an algorithm regarding individual gut microbiome features. The IBS-SSS evaluation for pre- and post-intervention exhibited significant improvement (p < .02 and p < .001 for the standard IBS diet and personalized nutrition groups, respectively). While the IBS-SSS evaluation changed to moderate from severe in 78% (11 out of 14) of the personalized nutrition group, no such change was observed in the standard IBS diet group. A statistically significant increase in the Faecalibacterium genus was observed in the personalized nutrition group (p = .04). Bacteroides and putatively probiotic genus Propionibacterium were increased in the personalized nutrition group. The change (delta) values in IBS-SSS scores (before-after) in personalized nutrition and standard IBS diet groups are significantly higher in the personalized nutrition group. AI-based personalized microbiome modulation through diet significantly improves IBS-related symptoms in patients with IBS-M. Further large-scale, randomized placebo-controlled trials with long-term follow-up (durability) are needed. © 2022 ENBIOSIS Biotechnologies Limited. Published with license by Taylor & Francis Group, LLC.
dc.identifier.DOI-ID10.1080/19490976.2022.2138672
dc.identifier.issn19490976
dc.identifier.urihttp://akademikarsiv.cbu.edu.tr:4000/handle/123456789/12964
dc.language.isoEnglish
dc.publisherTaylor and Francis Ltd.
dc.rightsAll Open Access; Gold Open Access; Green Open Access
dc.subjectArtificial Intelligence
dc.subjectDiet
dc.subjectGastrointestinal Microbiome
dc.subjectHumans
dc.subjectIrritable Bowel Syndrome
dc.subjectRNA, Ribosomal, 16S
dc.subjectprobiotic agent
dc.subjectRNA 16S
dc.subjectRNA 16S
dc.subjectadult
dc.subjectArticle
dc.subjectartificial intelligence
dc.subjectbacterial microbiome
dc.subjectBacteroides
dc.subjectbody mass
dc.subjectclinical article
dc.subjectClostridiaceae
dc.subjectcohort analysis
dc.subjectcontrolled study
dc.subjectFaecalibacterium
dc.subjectfecal microbiota transplantation
dc.subjectfeces analysis
dc.subjectfemale
dc.subjectfluorometry
dc.subjectfollow up
dc.subjectgastrointestinal tract
dc.subjectgene sequence
dc.subjecthigh throughput screening
dc.subjecthigh throughput sequencing
dc.subjecthuman
dc.subjectirritable colon
dc.subjectmachine learning
dc.subjectmale
dc.subjectmiddle aged
dc.subjectmultivariate analysis of variance
dc.subjectpersonalized nutrition
dc.subjectpilot study
dc.subjectrank sum test
dc.subjectRuminococcaceae
dc.subjecttherapy effect
dc.subjectartificial intelligence
dc.subjectdiet
dc.subjectintestine flora
dc.subjectmicrobiology
dc.titleArtificial intelligence-based personalized diet: A pilot clinical study for irritable bowel syndrome
dc.typeArticle

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