Advances in computational techniques-particularly machine learning-have expanded opportunities to analyse early infant motor repertoires, especially in naturalistic settings. The aim of this study was to evaluate the strengths, limitations, and perfo... read more
Magnetic resonance imaging (MRI) is hard to categorize properly in terms of interclass similarity, there is data imbalance, and sensitive clinical decision-making: but the performance of convolutional neural networks (CNNs) highly relies on effective... read more
Disordered proteins play essential roles in myriad cellular processes, yet their structural characterization remains a major challenge due to their dynamic and heterogeneous nature. Here we present a community-driven initiative to address this proble... read more
Environmental monitoring and assessment
Mar 9, 2026
Although machine learning (ML) has been increasingly used to predict pesticide sorption, most existing models rely primarily on molecular and soil descriptors and rarely account for the influence of solution chemistry. This limitation reduces their r... read more
The use of digital twins is becoming a foundation for automation that will improve how industries handle and organize data about both virtual and physical things. It enables analyzing industrial data more seamlessly by merging the Internet of Things ... read more
Journal of imaging informatics in medicine
Mar 9, 2026
Synthetic image data has emerged as a powerful tool in artificial intelligence (AI) enabled medical image analysis, providing scalable solutions to challenges such as data scarcity, class imbalance, and privacy-preserving. Despite rapid advances, the... read more
Journal of imaging informatics in medicine
Mar 9, 2026
Histopathology plays a crucial role in the diagnosis of many diseases, especially cancers, for which the correct classification of tissue samples significantly influences treatments for patients. The growing use of artificial intelligence (AI) in dig... read more
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