Tech Xplore

Benchmarking framework reveals major safety risks of using AI in lab experiments

While artificial intelligence (AI) models have proved useful in some areas of science, like predicting 3D protein structures, ...

Machine learning can predict patients' responses to antidepressants—while disentangling drug and placebo effects

Depression is one of the most widespread mental health disorders worldwide, affecting approximately 4% of the global ...
Scientific Research Publishing

Implementing an Electrocardiogram Suite in the Emergency Department to Decrease Door-to-EKG Time ()

Implementing an Electrocardiogram Suite in the Emergency Department to Decrease Door-to-EKG Time ...

AI-Generated Mental Health Advice Must Shift From Discrete-Classifications To Continuous Multidimensional Psychological Analyses

Mental health is not to be reduced to simple discrete classifications, but that's what AI is doing to us. AI can be ...

Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025)

Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025) ...

Decoded rules of microRNA strand selection reveal conserved, programmable features

MicroRNAs, whose discovery was recognized with the 2025 Nobel Prize in Physiology or Medicine, are central regulators of gene ...

Taxonomies Alone Won’t Save Digital Advertising

Static labels, however meticulously mapped, will always struggle to reflect the dynamic nature of human culture.
IEEE

ML-Mamba: A Dual-Stream State Space Model with Atrous Scanning for Multi-Label Remote Sensing Image Classification

Abstract: Remote sensing images exhibit multi-semantic char acteristics with abundant geographical and contextual information. Although multi-label learning methods demonstrate remark able advantages ...
IEEE

Multilingual and Multi-Class Sentiment Classification Using Machine Learning, BERT, and GPT-4o-mini

Abstract: In this study, we investigate multilingual and multiclass sentiment classification by analyzing datasets in Turkish, English, and Italian. The proposed approach consists of three main stages ...