BACKGROUND: Ambient artificial intelligence scribes are increasingly used to reduce clinician burnout and cognitive load, although their impact on documentation time remains inconsistent across studies. Most existing real-world impact studies have be... read more
Emotion recognition stands as a complex and prominent challenge within contemporary artificial intelligence research. Deep learning on physiological signals has boosted emotion recognition, yet unimodal limits, ignored channel importance, and tempora... read more
BACKGROUND: Resource Constrained Situations (RCS) at Emergency Medical Dispatch centers where there are more patients requiring an ambulance than there are available ambulances are common. Machine Learning (ML) techniques offer a promising but largel... read more
Although conventional automated analysis of corneal specular microscopy images has historically been limited by reproducibility challenges in the presence of corneal guttae, recent advances in artificial intelligence (AI) have significantly enhanced ... read more
Medical applications of mathematical modeling, including machine learning models, knowledge graphs, and health digital twins, primarily involve the prediction of patient outcomes. This expert perspective examines how mathematical modeling can contrib... read more
The complex terrain and diverse management practices in tea-producing regions have resulted in highly fragmented tea plantation plots, posing challenges to precision cultivation, yield estimation, and ecological management. Although remote sensing te... read more
The structural complexity of triacylglycerols (TGs) and the positional specificity of carbon-carbon double bonds (C═C) within fatty acyl (FA) chains present a formidable challenge in structural lipidomics. Traditional tandem mass spectrometry (MS) ap... read more
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Mar 31, 2026
Segmenting individual instances of mitochondria from imaging datasets can provide rich quantitative information, but manual segmentation is prohibitively time-consuming-prompting the development of automated algorithms based on deep neural networks. ... read more
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