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

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

Traditional machine learning models for automatic information classification require retraining data for each task. Researchers have demonstrated that art data can be automatically classified with ...

Models using established cardiovascular disease risk factors had satisfactory predictive performance for 5-year CVD risk in ...

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

Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting expertise.From neural networks to N ...

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...

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 ...

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