Usefulness of Machine Learning-Based Gut Microbiome Analysis for Identifying Patients with Irritable Bowels Syndrome

Usefulness of Machine Learning-Based Gut Microbiome Analysis for Identifying Patients with Irritable Bowels Syndrome

Irritable bowel syndrome (IBS) is diagnosed by subjective clinical symptoms. We aimed to establish an objective IBS prediction model based on gut microbiome analyses employing machine learning. We collected fecal samples and clinical data from 85 adult patients who met the Rome III criteria for IBS,...

Full description

Bibliographic Details
Main Authors: Hirokazu Fukui, Akifumi Nishida, Satoshi Matsuda, Fumitaka Kira, Satoshi Watanabe, Minoru Kuriyama, Kazuhiko Kawakami, Yoshiko Aikawa, Noritaka Oda, Kenichiro Arai, Atsushi Matsunaga, Masahiko Nonaka, Katsuhiko Nakai, Wahei Shinmura, Masao Matsumoto, Shinji Morishita, Aya K. Takeda, Hiroto Miwa
Format: Article
Language:English
Published: MDPI AG 2020-07-01
Series:Journal of Clinical Medicine
Subjects:
IBS
gut microbiome
short-chain fatty acids
machine learning
Online Access:https://www.mdpi.com/2077-0383/9/8/2403

Internet

https://www.mdpi.com/2077-0383/9/8/2403

Similar Items