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Machine Learning and Canine Chronic Enteropathies: A New Approach to Investigate FMT Effects

Innocente G, Patuzzi I, Furlanello T, Di Camillo B, Bargelloni L, Giron MC, Facchin S, Savarino E, Azzolin M, Simionati B. Machine Learning and Canine Chronic Enteropathies: A New Approach to Investigate FMT Effects. Vet. Sci. 2022, 9(9), 502.


This study evaluated the effects of oral freeze-dried fecal microbiota transplantation (FMT) in dogs with chronic enteropathies (CE). Clinical improvement was seen in 74% of dogs, with a significant decrease in Canine Chronic Enteropathy Clinical Activity Index (CCECAI) scores. Microbiome diversity metrics showed alpha and beta diversity changes between pre- and post-FMT samples, although responses varied among individual dogs. Machine learning algorithms accurately predicted diseased and healthy states based on microbial composition, demonstrating the potential for AI in analyzing complex microbiome data.

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