Researchers developed and validated a machine-learning algorithm for predicting nutritional risk in patients with nasopharyngeal carcinoma.

Machine learning tools can accelerate all stages of materials discovery, from initial screening to process development.

With a strong start to fiscal 2026, NetraMark is reiterating its previously stated guidance of achieving C$8–$10 million in booked contract backlog by mid-2026. This outlook is ...

Across generations, the meaning of work has shifted—from fields to factories, typewriters to laptops—yet human hands have ...

NetraMark Holdings Inc. (the "Company" or "NetraMark") (CSE: AIAI) (OTCQB: AINMF) (Frankfurt: PF0) a premier artificial intelligence (AI) company that is transforming ...

Across generations, the meaning of work has shifted—from fields to factories, typewriters to laptops—yet human hands have ...

The vote on Flock’s license plate readers capped months of whiplash, tensions, a 10-minute video, and discourse over a ...

Researchers in the Nanoscience Center at the University of Jyväskylä, Finland, have developed a pioneering computational ...

The quality of AI-generated artifacts and answers improves when certificates are demanded, even if the evidence provided by ...

In a new study published in The Crop Journal on November 7, researchers developed an AI model named TillerPET that enables ...