Researchers at the University at Buffalo have developed AudioSight, a smartphone-based screening platform that objectively assesses hearing-related disorders using pupil responses to sound. The system combines a low-cost 3D-printed smartphone attachment, near-infrared illumination, and artificial intelligence to analyze audio-evoked pupillary responses. Advanced machine learning models process features such as response latency, dilation speed, and recovery time to generate risk scores for conditions including hidden hearing loss, tinnitus, and hyperacusis. Designed for self-administration and remote use, the technology could expand access to hearing screening for children, older adults, cognitively impaired individuals, and underserved populations. The TRL 6 technology is available for licensing or collaboration. AudioSight could make hearing-disorder screening more accessible, affordable, and objective by enabling at-home assessment and teleaudiology services. Earlier identification of hearing disorders may improve treatment outcomes, reduce barriers to care, and support populations that have difficulty completing conventional hearing tests.

Three simple cleaning methods reduced bacterial levels on used single-use medical devices, according to a study from the University of Gothenburg. The findings could prove useful as a last-resort measure during severe shortages of medical supplies in a crisis or war.

A new understanding of antibiotic resistance could transform the diagnosis and treatment of humans and animals and help combat the global threat of antibiotic resistance more effectively.