Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.

This model was trained and tested on a 70%/30% split (train/test result cohort), achieving an area under the receiver operator curve on the test set of 0.866 (95% CI, 0.857 to 0.875). Assigning a ...

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

Systems controlled by next-generation computing algorithms could give rise to better and more efficient machine learning products, a new study suggests. Systems controlled by next-generation computing ...

A University of Hawaiʻi at Mānoa student-led team has developed a new algorithm to help scientists determine direction in ...

The development of humans and other animals unfolds gradually over time, with cells taking on specific roles and functions via a process called cell fate determination. The fate of individual cells, ...

Dynamic combined monitoring of SII and PNI in evaluating the prognostic impact on advanced driver gene–negative NSCLC patients receiving immunotherapy. This is an ASCO Meeting Abstract from the 2025 ...

6G visions include immersive extended reality, holographic communications, tactile internet applications, and large-scale digital twins. Supporting these services will demand fully autonomous network ...

Lithium-ion batteries have become the quiet workhorses of the energy transition, but the way they are designed and tested has ...