Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...

A research team has introduced a lightweight artificial intelligence method that accurately identifies wheat growth stages ...

When scientists test algorithms that sort or classify data, they often turn to a trusted tool called Normalized Mutual Information (or NMI) to measure how well an algorithm's output matches reality.

The collaboration features STRADVISION's SVNet FrontVision solution, demonstrated through a video-driven reference ...

By transferring temporal knowledge from complex time-series models to a compact model through knowledge distillation and attention mechanisms, the ...

Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive ...

What Are Non-Human Identities (NHIs) and Why Do They Matter for Enterprise Security? Cybersecurity is continually shifting, with machine identities, or Non-Human Identities (NHIs), emerging as a ...

Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...

Reverse Logistics, Artificial Intelligence, Circular Economy, Supply Chain Management, Sustainability, Machine Learning Share and Cite: Waditwar, P. (2026) De-Risking Returns: How AI Can Reinvent Big ...

Objectives In patients with chronic obstructive pulmonary disease (COPD), severe exacerbations (ECOPDs) impose significant morbidity and mortality. Current guidelines emphasise using ECOPD history to ...

New findings highlight the need to systematically check for bias in pathology AI to ensure equitable care for patients.

APA has a mental health evaluation framework. I opted to augment the framework with an added focus on AI. Makes sense and is ...