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 ...

Net, a hybrid model that improves energy consumption prediction in low-energy buildings, enhancing accuracy and ...

The financial landscape of 2026 is defined by a paradox: machine learning systems are now more powerful and autonomous than ever, yet they operate under the strictest regulatory scrutiny in history.

Ligand-based drug design combines AI and QSAR modeling to prioritize drug candidates, minimizing preclinical failures and ...

AI meets isotope science: Machine learning is enhancing isotope analysis techniques, improving efficiency, accuracy, and insights into geochemical processes. Key hurdles remain: Data scarcity, limited ...

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 ...

Background Tobacco use remains a global public health challenge, leading to over 8 million annual deaths and significant ...

Tabular data—structured information stored in rows and columns—is at the heart of most real-world machine learning problems, from healthcare records to financial transactions. Over the years, models ...

Artificial intelligence is rapidly changing the job market, automating jobs across industries. Therefore, in such a scenario, upskilling oneself in industry-relevant AI skills becomes even more ...

Solid‑state hydrogen storage offers high density and safety, but material development is slow. A comprehensive review ...

ABSTRACT: Monitoring of natural resources is a major challenge that remote sensing tools help to facilitate. The Sissili province in Burkina Faso is a territory that includes significant areas ...