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.
A new study reveals why a highly infectious variant of the cholera bug, which caused large disease outbreaks in the early 1990s, did not cause the eighth cholera pandemic as feared – but instead unexpectedly disappeared.
University of Rhode Island College of Engineering Professor Ali Shafqat Akanda and a team of researchers have developed an application for smartphones called CholeraMap to serve as an early warning device for cholera.