Listen to the Toilet — It Could Detect Disease #ASA183

Researchers describe how a noninvasive microphone sensor could identify bowel diseases without collecting any identifiable information. They tested the technique on audio data from online sources, transforming each audio sample of an excretion event into a spectrogram, which essentially captures the sound in an image. The images were fed to a machine learning algorithm that learned to classify each event based on its features. The algorithm’s performance was tested against data with and without background noises.

Study: Obesity Associated with Abnormal Bowel Habits – Not Diet

Researchers at Beth Israel Deaconess Medical Center demonstrated for the first time that a strong association between obesity and chronic diarrhea is not driven by diet or physical activity. The findings could have important implications for how physicians might approach and treat symptoms of diarrhea in patients with obesity differently.