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Empowering individuals to adopt artificial intelligence for health information seeking: A latent profile analysis among users in Hong Kong.

Social science & medicine (1982)
RATIONALES: Using AI for health information seeking is a novel behavior, and as such, developing effective communication strategies to optimize AI adoption in this area presents challenges. To lay the groundwork, research is needed to map out users' ...

Exploring trade-offs in equitable stroke risk prediction with parity-constrained and race-free models.

Artificial intelligence in medicine
A recent analysis of common stroke risk prediction models showed that performance differs between Black and White subgroups, and that applying standard machine learning methods does not reduce these disparities. There have been calls in the clinical ...

Factors influencing the estimation of phacoemulsification procedure time in cataract surgery: Analysis using neural networks.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Realistic and accurate estimation of the surgery duration is one of the key factors influencing the optimization of hospital work and, consequently, the planning and management of the budget. In the present study, the author...

Identifying the key predictors of positive self-perceptions of aging using machine learning.

Social science & medicine (1982)
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...

Non-invasive diagnosis of lung diseases via multimodal feature extraction from breathing audio and chest dynamics.

Computers in biology and medicine
Early and accurate diagnosis of lung diseases is crucial for effective treatment. While traditional methods have limitations, audio analysis offers a promising non-invasive approach. However, existing studies often rely solely on acoustic features, n...

Expanded AI learning: AI as a Tool for Human Learning.

Academic radiology
RATIONALE AND OBJECTIVES: To demonstrate that a deep learning (DL) model can be employed as a teaching tool to improve radiologists' ability to perform a subsequent imaging task without additional artificial intelligence (AI) assistance at time of im...

A computed tomography-based deep learning radiomics model for predicting the gender-age-physiology stage of patients with connective tissue disease-associated interstitial lung disease.

Computers in biology and medicine
OBJECTIVES: To explore the feasibility of using a diagnostic model constructed with deep learning-radiomics (DLR) features extracted from chest computed tomography (CT) images to predict the gender-age-physiology (GAP) stage of patients with connecti...

Automatic implicit motive codings are at least as accurate as humans' and 99% faster.

Journal of personality and social psychology
Implicit motives, nonconscious needs that influence individuals' behaviors and shape their emotions, have been part of personality research for nearly a century but differ from personality traits. The implicit motive assessment is very resource-inten...

Electroencephalography estimates brain age in infants with high precision: Leveraging advanced machine learning in healthcare.

NeuroImage
Changes in the pace of neurodevelopment are key indicators of atypical maturation during early life. Unfortunately, reliable prognostic tools rely on assessments of cognitive and behavioral skills that develop towards the second year of life and afte...

Therapeutic effect and concomitant toxicity of hydrargyrum chloratum compositum on chronic difficult-to-heal wounds in rats.

Journal of ethnopharmacology
ETHNOPHARMACOLOGICAL RELEVANCE: Hydrargyrum chloratum compositum(Hcc) is a traditional Chinese medicine for external use, with the efficacy of 'transforming corrosion and pulling out toxins, removing corrosion and regenerating muscles'. The main comp...