American public opinion on artificial intelligence in healthcare.

Billions of dollars are being invested into developing medical artificial intelligence (AI) systems and yet public opinion of AI in the medical field seems to be mixed. Although high expectations for the future of medical AI do exist in the American public, anxiety and uncertainty about what it can do and how it works is widespread. Continuing evaluation of public opinion on AI in healthcare is necessary to ensure alignment between patient attitudes and the technologies adopted.

Quantifying Healthy Aging in Older Veterans Using Computational Audio Analysis.

Background: Researchers are increasingly interested in better methods for assessing the pace of aging in older adults, including vocal analysis. The present study sought to determine whether paralinguistic vocal attributes improve estimates of the age and risk of mortality in older adults.

Methods: To measure vocal age, we curated interviews provided by male U.

Explainable automated evaluation of the clock drawing task for memory impairment screening.

Introduction: The clock drawing task (CDT) is frequently used to aid in detecting cognitive impairment, but current scoring techniques are time-consuming and miss relevant features, justifying the creation of an automated quantitative scoring approach.

Methods: We used computer vision methods to analyze the stored scanned images ( = 7,109), and an intelligent system was created to examine these files in a study of aging World Trade Center responders. Outcomes were CDT, Montreal Cognitive Assessment (MoCA) score, and incidence of mild cognitive impairment (MCI).

Diet modulates brain network stability, a biomarker for brain aging, in young adults.

Epidemiological studies suggest that insulin resistance accelerates progression of age-based cognitive impairment, which neuroimaging has linked to brain glucose hypometabolism. As cellular inputs, ketones increase Gibbs free energy change for ATP by 27% compared to glucose. Here we test whether dietary changes are capable of modulating sustained functional communication between brain regions (network stability) by changing their predominant dietary fuel from glucose to ketones.

Latent human traits in the language of social media: An open-vocabulary approach.

Over the past century, personality theory and research has successfully identified core sets of characteristics that consistently describe and explain fundamental differences in the way people think, feel and behave. Such characteristics were derived through theory, dictionary analyses, and survey research using explicit self-reports. The availability of social media data spanning millions of users now makes it possible to automatically derive characteristics from behavioral data-language use-at large scale.