Use of Hearing Aids Embedded with Inertial Sensors and Artificial Intelligence to Identify Patients at Risk for Falling.

Objective: To compare fall risk scores of hearing aids embedded with inertial measurement units (IMU-HAs) and powered by artificial intelligence (AI) algorithms with scores by trained observers.

Study Design: Prospective, double-blinded, observational study of fall risk scores between trained observers and those of IMU-HAs.

Setting: Tertiary referral center.

Toward Alleviating the Stigma of Hearing Aids: A Review.

Despite the significant advancements in hearing aid technology, their adoption rates remain low, with stigma continuing to be a major barrier for many. This review aims to assess the origins and current state of hearing aid stigma, as well as explore potential strategies for alleviating it. This review examines the societal perceptions, psychological impacts, and recent technological advancements that can influence hearing aid adoption and reduce stigma.

EEG-based brain age prediction in infants-toddlers: Implications for early detection of neurodevelopmental disorders.

The infant brain undergoes rapid developmental changes in the first three years of life. Understanding these changes through the prediction of chronological age using neuroimaging can provide insights into typical and atypical brain development. We utilized 938 resting-state EEG recordings from 457 typically developing infants, 2 to 38 months old, to develop age prediction models.

Dysregulated RNA splicing induces regeneration failure in alcohol-associated liver disease.

Individuals with progressive liver failure are at a high risk of mortality without liver transplantation. However, our understanding of derailed regenerative responses in failing livers is limited. Here, we performed comprehensive multi-omic profiling of healthy and diseased human livers using bulk and single-nucleus RNA-plus ATAC-seq.