利用基于人工智能的 BERTopic 模型对 PubMed 摘要中与肠道微生物群和肠道脑轴相关的神经精神疾病进行主题建模

Ashok Kumar , Avi Karamchandani , Sourabh Singh
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引用次数: 0

摘要

肠道微生物群在肠道系统与中枢神经系统之间复杂的肠脑轴相互作用中发挥着至关重要的作用。肠道与大脑之间错综复杂的双向交流网络,通过神经、激素和免疫途径进行调解,即所谓的肠脑轴,已被认为与多种精神、神经和行为疾病的病理生理学有关。肠道微生物群组成的改变或菌群失调与阿尔茨海默病、帕金森病、多发性硬化症、自闭症谱系障碍、缺血性中风、饮食失调、抑郁、焦虑、压力和成瘾等疾病有关。在这项研究中,基于人工智能的自然语言处理技术,使用专门从事主题建模的 Transformer 模型 BERT,将 Python 软件包 BERTopic 应用于从 2014 年到 2024 年 5 月发表的 3,482 篇 PubMed 文章的摘要,以探索肠道微生物群对精神、神经和行为疾病的影响。由于 BERTopic 的一个组件具有随机性,因此在 BERTopic 的单次运行中存在一些差异,但总体而言,发现的主题与主要的神经精神疾病相对应。为了了解结果变化的影响,我们在保持参数相同的情况下重复运行了十次 BERTopic。在 BERTopic 的所有十次重复运行中一致发现的主要主题包括抑郁症、阿尔兹海默病、自闭症谱系障碍、帕金森病、多发性硬化症、缺血性中风、神经性厌食症和精神分裂症。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Topic modeling of neuropsychiatric diseases related to gut microbiota and gut brain axis using artificial intelligence based BERTopic model on PubMed abstracts

Gut microbiota play a crucial role in complex interactions of the gut brain axis between the gastrointestinal system and the central nervous system. The intricate network of bidirectional communication between the gut and brain, mediated through neural, hormonal, and immunological pathways, known as the gut-brain axis, has been implicated in the pathophysiology of several mental, neurological and behavioral disorders. Alterations in the gut microbiota composition, or dysbiosis, have been associated with disorders like Alzheimer's disease, Parkinson's disease, Multiple Sclerosis, Autism Spectrum Disorder, Ischemic Stroke, Eating Disorders, depression, anxiety, stress and addiction. In this study, a Python package BERTopic, based on Artificial Intelligence based Natural Language Processing using Transformer model BERT, specializing in topic modeling, was applied to abstracts of 3,482 PubMed articles published from year 2014 until May 2024, to explore the mental, neurological, and behavioral diseases influenced by the gut microbiota. There were some variations in individual runs of BERTopic due to stochastic nature of one of its components, but overall the discovered topics corresponded to major neuropsychiatric diseases. To understand the impact of the variability in outcomes ten repeated runs of BERTopic were performed with keeping identical parameters. The major topics that were found consistently in all the ten repeated runs of BERTopic were Depression, Alzheimer Disease, Autism Spectrum Disorder, Parkinson's Disease, Multiple Sclerosis, Ischemic Stroke, Anorexia Nervosa and Schizophrenia.

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来源期刊
Neuroscience informatics
Neuroscience informatics Surgery, Radiology and Imaging, Information Systems, Neurology, Artificial Intelligence, Computer Science Applications, Signal Processing, Critical Care and Intensive Care Medicine, Health Informatics, Clinical Neurology, Pathology and Medical Technology
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