Abstract: This study investigates the application of machine learning in sleep health analytics. It focuses on classification problems relevant to the detection of sleep disorders with a view to ...

The role of machine learning and deep learning in wildfire prediction remains limited by geographic concentration, uneven ...

AI dependence among university students is driven less by routine use and more by the reasons students turn to the technology ...

Yeshwanth Macha developed explainable AI models improving insurance fraud detection accuracy, transparency, compliance and ...

Artificial intelligence shows promise for improving care for peripheral artery disease through earlier detection, improved ...

Professor Kyungwho Choi's team of the School of Mechanical Engineering at Sungkyunkwan University, in collaboration with ...

Personalized algorithms may quietly sabotage how people learn, nudging them into narrow tunnels of information even when they start with zero prior knowledge. In the study, participants using ...

The landscape of spine rehabilitation is shifting rapidly in 2026, driven by fresh insights into the gut-disc axis, AI-driven diagnostics, and a renewed focus on functional resilience over imaging ...

Most public talk about AI focuses on large language models and flashy generative tools. But honestly, the most dependable ...

Proton exchange membrane fuel cells (PEMFCs) are promising for zero-emission vehicles, but their sub-zero start-up capability remains a major hurdle. Freezing of product water inside the membrane ...

Abstract: Accurate demand forecasting is a critical requirement in the dairy industry, where fluctuations in consumption, seasonal effects, and product perishability create significant operational ...