Technology advances in DNA sequencing and more sophisticated data-analytics tools has led to extensive research on the relationship between the microbiome and diseases. Researchers are developing a machine learning-based approach to distinguish the type of cancer by analyzing the tissue-specific microbial information, according to the July 21, 2023 issue of Nature.com (1).
Random Forest models of five types of cancers from the Cancer Microbiome Atlas database, achieved promising performances when predicting head and neck, stomach, and colon cancer cases, with the latter showing 90% accuracy across the different studies conducted, says the Nature article. The random forest method forms multiple decision trees in machine learning by regression classification task outputs (2).
This research shows the potential of adopting machine learning techniques in predicting disease and cancer.
1. https://www.nature.com/articles/s41598-023-38670-0
2. https://en.m.wikipedia.org/wiki/Random_forest
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