image:  The researchers developed a machine learning model that integrates data from carbon-supported single-atom catalysts and perovskite oxide catalysts. The model predicts the activity of a new material class that was not included in training: single-atom catalysts supported on perovskite oxides. The surface atomic arrangement of the catalyst is learned as image information, while the

Standard methods for diagnosing lung diseases often only detect problems once damage has already occurred. Learn how AI-driven lung imaging technologies can provide a way to identify disease earlier, allowing for more targeted interventions Respiratory diseases remain a leading cause of morbidity and mortality worldwide, (1) yet our ability to detect and monitor lung disease

Teachers in higher-needs schools were less likely than those in wealthier schools to have received guidelines, echoing previous research.

Abstract Women, especially pregnant women, have historically been excluded from clinical research. In this News and Perspectives article, JMIR Correspondent Michelle Falci reports on how advances in data analytics may help bridge evidence gaps. Key Takeaways: Using large datasets and machine learning, researchers aim to close evidence gaps in drug safety created by excluding pregnant

agent system seriously fail in production, it wasn’t dramatic. There was no crash. No error message. The system just kept running and producing outputs that looked reasonable until someone actually read them carefully enough to notice something was off. When we decided to look into it, it took us two days’ worth of debugging to

Article Open access Published: 27 May 2026 K. Nithya1 & C. R. Dhivyaa1  Scientific Reports (2026) Cite this article We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content

Spoiler: Tons of public companies are already using and selling AI technology. Samuel Boivin / Shutterstock How far are we from AI public companies? The truth is that there are already publicly traded companies that build artificial intelligence tools, sell the hardware behind them or use AI so deeply that it shapes their business. For

If I had to pick one artificial intelligence (AI) stock to buy today, bury in a time capsule, and not peek at again until 2036, I wouldn't choose a chip designer or a model-maker. I wouldn't choose Nvidia, Nebius Group, or any other sexy, hot name right now. Those businesses are great, but they operate