Artificial Intelligence Analyzes Gut Microbiota of Fish to Detect Waters Compromised by Climate Change

Article title: Gut microbiota of wild fish as reporters of compromised aquatic environments sleuthed through machine learning

Authors: John W. Turner Jr., Xi Cheng, Nilanjana Saferin, Ji-Youn Yeo, Tao Yang Bina Joe

From the authors: “Overall, this study represents the first multispecies stress-related comparison of its kind and demonstrates the potential of artificial intelligence via [machine learning] as a tool for biomonitoring and detecting compromised aquatic conditions.”

This study is highlighted as one of June’s “best of the best” as part of the American Physiological Society’s APSselect program.