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

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

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) ...

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

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

The advancement of artificial intelligence (AI) algorithms has opened new possibilities for the development of robots that ...

As AI models grow more complex, a new white-collar gig workforce has emerged to review and guide systems. A new category of ...

Introduction: Why Data Quality Is Harder Than Ever Data quality has always been important, but in today’s world of ...

Legit at-home jobs are not limited to corporate payrolls or gig apps. Many people now build résumés, portfolios, and professional networks through structured remote roles that look and feel like work, ...

Abstract: This study compares the relative utility of deep learning models as automated phenotypic classifiers, built with features of peripheral blood cell populations assayed with flow cytometry. We ...

Colon cancer classification has a significant guidance value in clinical diagnoses and medical prognoses. The classification of colon cancers with high accuracy is the premise of efficient treatment.