Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 17,051 to 17,060 of 213,633 articles

A Doubly Robust Machine Learning Procedure to Estimate Disparities by Race/Ethnicity and Sex in the Relationship Between Adverse Childhood Experiences and Suicidality.

Journal of the American Academy of Child and Adolescent Psychiatry
OBJECTIVE: Suicide is a leading cause of death among youth, and adverse childhood experiences (ACEs) are established risk factors for suicidality. This study is the first to investigate disparities in the cumulative impact of ACEs on suicidal ideatio... read more 

DivideFold+: an AI-based tool for RNA secondary structure prediction with subdomains identification and visualization and data augmentation.

Journal of molecular biology
Predicting the secondary structure of RNAs, particularly long RNAs, remains a challenging problem despite its importance in identifying the structural roles of RNAs. Deep-learning-based methods face a lack of data and cannot provide very accurate pre... read more 

Few-shot learning-driven discovery of Lutein suppresses Th1-mediated inflammation via glucose metabolism.

Acta pharmacologica Sinica
The discovery of selective immunosuppressants for T cell-mediated diseases like Ulcerative Colitis (UC) is a significant challenge. While traditional screening is inefficient, Artificial intelligence (AI)-driven approaches are often hindered by the s... read more 

Demographic and emission drivers of household air pollution in biomass using communities.

Scientific reports
This study investigates household air pollution from biomass combustion by integrating a household survey, experimental stove testing, and data-driven analysis. A structured survey of 1200 households captured socio-economic conditions, cooking practi... read more 

Construction of a multi-dimensional predictive model for college students' academic performance based on deep learning.

Scientific reports
Academic performance (AP) prediction is crucial for recognizing at-risk students and enhancing learning outcomes. Traditional statistical models often fail to capture temporal and behavioral patterns. Deep learning (DL) approaches offer improved accu... read more 

Interpretable machine learning and signal processing for automated reading and quality control of lateral flow tests for schistosomiasis.

Nature communications
There is a lack of automated pipelines for diagnostic classification of point-of-care tests for neglected tropical diseases. Here, we present an end-to-end automated pipeline for the analysis of point-of-care circulating cathodic antigen tests for sc... read more 

Machine-learning algorithms to identify key practices contributing to variation in biosecurity levels on Japanese commercial swine farms.

The Journal of veterinary medical science
Transboundary diseases, such as African swine fever, pose significant threats to the Japanese swine industry, making robust biosecurity essential. However, established assessment tools quantify overall biosecurity levels, and the specific practices d... read more 

Development and validation of a logistic regression model for predicting visual impairment in middle-aged and older adults with diabetes: results from the China Health and Retirement Longitudinal Study.

International journal of ophthalmology
AIM: To develop and validate a clinician-friendly logistic regression prediction model for self-reported visual impairment (VI) in middle-aged and older adults (≥45y) with diabetes. METHODS: Leveraging data from the China Health and Retirement Longit... read more 

Content-Style Identification via Differential Independence

arXiv
Generative analysis often models multi-domain observations as nonlinear mixtures of domain-invariant content variables and domain-specific style variables. Identifying both factors from unpaired domains enables tasks such as domain transfer and count... read more