Artificial Intelligence Medical Compendium

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

Showing 29,441 to 29,450 of 219,931 articles

A systematic comparison of transformers and ConvNets for root segmentation across nine datasets.

Plant methods
BACKGROUND: Root segmentation is a fundamental yet challenging task in image-based plant phenotyping. Accurate segmentation is a prerequisite for extracting root traits relevant to plant physiology, breeding, and agronomy. While U-Net and other convo... read more 

Deep learning driven clustering of post-traumatic stress disorder (PTSD) profiles in student-athletes: implications for precision and stratified mental health support.

BMC psychology
BACKGROUND: Athletes frequently experience potentially traumatic events related to sports injuries, significantly increasing their risk of developing post-traumatic stress disorder (PTSD). However, existing assessment methods often overlook the heter... read more 

Decoding stress resilience in soybean: Regulatory networks and precision breeding under climate change.

Journal of integrative plant biology
Soybean (Glycine max L.), a key global source of protein and oil, is increasingly threatened by climate change-driven environmental stresses, including drought, salinity, waterlogging, temperature extremes, nutrient limitations, and pathogen pressure... read more 

Turbocharging crop breeding with integrated biotechnology for a climate-resilient future.

Journal of integrative plant biology
Global agriculture faces unprecedented challenges from climate change and population growth, creating an urgent demand for the rapid development of resilient and high-yielding crop varieties. Although conventional breeding has achieved substantial pr... read more 

Community Characteristics Predict Local News Agenda Building About Racial Health Disparities.

Health communication
We examined market-level social and demographic characteristics and station-level factors as predictors of local television news coverage of COVID-19-related racial disparities using the theoretical lens of agenda building and the community structure... read more 

Can Algorithms Efficiently Identify Interpretable and Persuasive Message Features? An Agnostic Causal Machine Learning Approach.

Health communication
Argument strength and message persuasiveness are key constructs in message effects research. Yet, researchers still lack a systematic and efficient approach to uncover the "recipe" for these message-level latent features. We applied an agnostic causa... read more