Researchers developed NiCLIP, an AI model that decodes cognitive tasks, concepts, and domains from brain activation patterns. Trained on over 23,000 papers, NiCLIP excels at group-level decoding, ...

Changes in our genes affect health risks from heart disease to cancer, but how those genes are turned on and off is just as ...

A new leakage-controlled machine learning framework achieves strong sentiment classification on social media data while ...

Understanding the properties of different materials is an important step in material design. X-ray absorption spectroscopy (XAS) is an important technique for this, as it reveals detailed insights ...

A simulation study reported machine-learning predictions of bearing-capacity and safety factors for ring foundations in ...

Dropping AI Discovery Reveals Why Bacteria Resist Treatment”, “content”: “ For decades, our approach to fighting bacterial ...

Among ventilated adults who underwent extubation, 18.7% were high risk for extubation failure per machine learning even though they met traditional low-risk criteria, according to data presented at ...

Polymers such as polypropylene are fundamental materials in the modern world, found in everything from computers to cars. Because of their ubiquity, it's vital that materials scientists know exactly ...

Chemists routinely optimize reactions to maximize the yield of their desired products, but understanding why those reactions work can require laborious experiments that track reactions through time.

Utilizing machine learning to assess distinct depressive symptoms improves the identification of adults with suicidal ideation.