Machine learning-based approaches for cancer prediction using microbiome data.

ABSTRACT: Emerging evidence of the relationship between the microbiome composition and the development of numerous diseases, including cancer, has led to an increasing interest in the study of the human microbiome. Technological breakthroughs regarding DNA sequencing methods propelled microbiome studies with a large number of samples, which called for the necessity of more sophisticated data-analytical tools to analyze this complex relationship. The aim of this work was to develop a machine learning-based approach to distinguish the type of cancer based on the analysis of the tissue-specific microbial information, assessing the human microbiome as valuable predictive information for cancer identification. For this purpose, Random Forest algorithms were trained for the classification of five types of

SUBMITTER: Freitas P 

PROVIDER: S-EPMC10362018 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature