Researchers at UC San Diego have developed advanced deep learning techniques that could revolutionize treatment planning for breast cancer radiotherapy – making it faster and improving its quality.

Artificial intelligence and machine learning are no longer abstract concepts confined to academic discussions but stand at ...

Unlike earlier large language models (LLMs) that primarily pattern-matched from training data, reasoning models represent a fundamental shift from statistical prediction to structured problem-solving.

Lightning is one of the primary causes of transmission line trips, posing a significant threat to the safety of power grids.

Peptides designed by artificial intelligence restrict both drug-resistant bacteria and rapidly evolving viruses.

Major depressive disorder (MDD) is a serious mental health condition that impacts individuals of all ages, including children ...

Few professionals have navigated the complex journey from legacy systems to modern architectures as successfully as Sai Kiran Malikireddy, who represents a new generation of technical leaders who ...

Traditional methods for identifying therapeutic gene targets, crucial for personalized medicine, are expensive and ...

Identifying therapeutic gene targets is essential for advancing personalized medicine and addressing the genetic basis of ...

On the heels of the release of TigerGraph Savanna, the most innovative cloud native graph database platform for supercharging AI systems, TigerGraph continues to lead the market as the ...

A new deep space-time generative graph convolutional autoencoder is introduced to address these shortcomings. The proposed framework captures both spatial and temporal characteristics of the PDS using ...

Advances in graph machine learning (ML) have been driven by applications in chemistry as graphs have remained the most expressive representations of molecules. This has led to progress within both ...