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Big data approaches for novel mechanistic insights on sleep and circadian rhythms: a workshop summary.
Sleep
Jun 13, 2025
The National Center on Sleep Disorders Research of the National Heart, Lung, and Blood Institute at the National Institutes of Health hosted a 2-day virtual workshop titled Big Data Approaches for Novel Mechanistic Insights on Disorders of Sleep and ...
New case law and liability risks for manufacturers of medical AI.
Science (New York, N.Y.)
Jun 12, 2025
Recent case law can shape how innovation unfolds.
Toward AI-Driven Precision Measurement of Cognition, Behavior, and Psychological Function in Aging and Alzheimer's Disease and Alzheimer's Disease-Related Dementias.
The journals of gerontology. Series B, Psychological sciences and social sciences
Jun 10, 2025
The National Institute on Aging (NIA) is at the forefront of leveraging advances in artificial intelligence (AI) to better understanding of aging and the diagnosis and treatment of Alzheimer's Disease (AD) and Alzheimer's disease-related dementias (A...
Deciphering Key Features of Social Resilience Versus Social Vulnerability in Later Life: A Biopsychosocial Model of Social Asymmetry.
The journals of gerontology. Series B, Psychological sciences and social sciences
Jun 10, 2025
OBJECTIVES: Confronted with shrinking social networks, older adults exhibit individual differences in social adaptability, reflected as socially resilient versus socially vulnerable. The purpose of this study was to examine key features that reflect ...
Using Machine Learning to Identify Predictors of Maternal and Infant Hair Cortisol Concentration Before and During the COVID-19 Pandemic.
Stress and health : journal of the International Society for the Investigation of Stress
Jun 1, 2025
Hair cortisol concentration (HCC) has been theorized to reflect chronic stress, and maternal and infant HCC may be correlated due to shared genetic, physiological, behavioural, and environmental factors, such as stressful life circumstances. The curr...
Combining Machine Learning and Comparative Effectiveness Methodology to Study Primary Care Pharmacotherapy Pathways for Veterans With Depression.
Medical care
Jun 1, 2025
OBJECTIVES: To demonstrate an innovative method combining machine learning with comparative effectiveness research techniques and to investigate a hitherto unstudied question about the effectiveness of common prescribing patterns.
Identifying the key predictors of positive self-perceptions of aging using machine learning.
Social science & medicine (1982)
Jun 1, 2025
This study aimed to identify key predictors of self-perceptions of aging (SPA) among older adults by examining a comprehensive set of potential predictors across physical, psychological, social, and demographic domains. Data from over 4000 American a...
Exploring multivariate machine learning frameworks to parallelize PM simultaneous estimations across the continental United States.
Environmental pollution (Barking, Essex : 1987)
Jun 1, 2025
Fine particulate matter (PM2.5) comprises diverse chemical components, including elemental carbon (EC), silicon (SI), sulfate (SO), and calcium (CA), each linked to varied health and environmental impacts. Accurately estimating these components' spat...
Comparative analysis of GPT-4 and Google Gemini's consistency with pediatric otolaryngology guidelines.
International journal of pediatric otorhinolaryngology
Jun 1, 2025
OBJECTIVE: To evaluate the accuracy and completeness of large language models (LLMs) in interpreting pediatric otolaryngology guidelines.
Machine learning-based prediction of hearing loss: Findings of the US NHANES from 2003 to 2018.
Hearing research
Jun 1, 2025
The prevalence of hearing loss (HL) has emerged as an escalating public health concern globally. The objective of this study was to leverage data from the National Health and Nutritional Examination Survey (NHANES) to develop an interpretable predict...
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