Schizophrenia is a severe and often highly debilitating psychiatric disorder characterized by distorted emotions, thinking ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...

Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving ...

Machine learning holds great promise for classifying and identifying fossils, and has recently been marshaled to identify trackmakers of dinosaur ...

From fine-tuning open source models to building agentic frameworks on top of them, the open source world is ripe with ...

Abstract: Advancements in machine learning (ML) have facilitated the prediction of key aspects of human locomotion, particularly in identifying subject gait trajectories essential for recognizing ...

There is often no straightforward explanation for the various types of violence that occur around the world. In fact, even when using clear definitions (such as “Civil War,” “Invasion,” or “Local ...

Dr Michele Orini shares how machine learning can help identify critical VT ablation targets for a safer, data-driven ...

Assistant Professor Yupeng Zhang and his team, along with researchers from the University of California, Irvine, received a ...

Background Suicide rates have increased over the last couple of decades globally, particularly in the United States and among populations with lower economic status who present at safety-net ...

This project focuses on building and evaluating machine learning (ML) classification models to predict whether a person has diabetes based on medical and demographic features. It was developed as an ...