In order for patients to be treated for cholera, they must know that they have the disease first. However, it can be a sensitive and difficult task to monitor bowel diseases, such as cholera. Maia Gatlin, a research engineer at the Georgia Institute of Technology, created a way to use artificial intelligence to detect diarrhea. She calls her presentation The Feces Thesis: Using Machine Learning to Detect Diarrhea.
A noninvasive microphone sensor can detect disease in bowels
Gatlin will be presenting her thesis and the sensor tool today, Dec. 5, at the annual Meeting of the Acoustical Society of America, explaining her findings on how machine learning can be used to detect diseases in the bowel. She uses a noninvasive microphone sensor to identify bowel diseases, without necessarily collecting identifiable information, meaning the AI can determine the infection without having to be examined in a medical facility to collect additional data.