Medical history predicts phenome-wide disease onset and enables the rapid response to emerging health threats.

The COVID-19 pandemic exposed a global deficiency of systematic, data-driven guidance to identify high-risk individuals. Here, we illustrate the utility of routinely recorded medical history to predict the risk for 1741 diseases across clinical specialties and support the rapid response to emerging health threats such as COVID-19. We developed a neural network to learn from health records of 502,489 UK Biobank participants.

Association of Auditory Interference and Ocular-Motor Response with Subconcussive Head Impacts in Adolescent Football Players.

The aim of this study was to examine whether neuro-ophthalmological function, as assessed by the King-Devick test (KDT), alters during a high school football season and to explore the role of auditory interference on the sensitivity of KDT. During the 2021 and 2022 high school football seasons, football players' neuro-ophthalmological function was assessed at five time points (preseason, three in-season, postseason), whereas control athletes were assessed at preseason and postseason. Two-hundred ten football players and 80 control athletes participated in the study.

Portable through-metal ultrasonic power transfer using a dry-coupled detachable transmitter.

Ultrasonic waves can be used to transfer power and data efficiently through metallic enclosures when feedthroughs are not practical due to structural or electromagnetic shielding considerations. Previous implementations of ultrasonic power transfer (UPT) used a piezoelectric transducer permanently bonded to the metal for efficient ultrasonic coupling. For portable operation, it is essential to have a detachable transmitter (charger) that is only attached to the enclosure while transferring power.

Medical history predicts phenome-wide disease onset and enables the rapid response to emerging health threats.

The COVID-19 pandemic exposed a global deficiency of systematic, data-driven guidance to identify high-risk individuals. Here, we illustrate the utility of routinely recorded medical history to predict the risk for 1883 diseases across clinical specialties and support the rapid response to emerging health threats such as COVID-19. We developed a neural network to learn from health records of 502,460 UK Biobank.