Machine learning based screening tool for Alzheimer’s disease via gut microbiome

• Pedro Velasquez ^[1] ; Mai Oudah ^[1]
  1. [1] New York University

     New York University

     Estados Unidos

     
• Localización: Practical applications of computational biology and bioinformatics, 17th International Conference (PACBB 2023) / Miguel Rocha (ed. lit.), Florentino Fernández Riverola (ed. lit.), Mohd Saberi Mohamad (ed. lit.), Ana Belén Gil González (ed. lit.), 2023, ISBN 978-3-031-38078-5, págs. 62-72
• Idioma: inglés
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• Resumen

  • As the connection between the gut and brain is further researched, more data has become available, allowing for the utilization of machine learning (ML) in such analysis. In this paper, we explore the relationship between Alzheimer’s disease (AD) and the gut microbiome and how it can be utilized for AD screening. Our main goal is to produce a reliable, noninvasive screening tool for AD. Several ML algorithms are examined separately with and without feature selection/engineering. According to the experimental results, the Naive Bayes (NB) model performs best when trained on a feature set selected by the correlation-based feature selection method, which significantly outperforms the baseline model trained on the original full feature space.