Technology Networks

AI and Machine Learning in High-Throughput Screening

Explore how AI in high-throughput screening improves drug discovery through advanced data analysis, hit identification and ...
IEEE

Fusion of Supervised Feature Selection and Unsupervised Clustering for Multinuclei Classification of MER Signals in DBS for Parkinson’s Disease

Abstract: In deep brain stimulation (DBS) surgery for Parkinson’s disease (PD), the accurate intraoperative identification of key nuclei—such as the subthalamic nucleus (STN)—is critical to ensuring ...
Frontiers

Machine learning–guided feature selection and predictive model construction for attention-deficit/hyperactivity disorder

A total of 8,598 children were enrolled and classified into three groups: ADHD (n=3,678), subthreshold ADHD (s-ADHD) (n=1,495), and healthy controls (HC) (n=3,425). Data collection covered 40 ...
unite

DINOv3 and the Future of Computer Vision: Self-Supervised Learning at Scale

Labeling images is a costly and slow process in many computer vision projects. It often introduces bias and reduces the ability to scale large datasets. Therefore, researchers have been looking for ...
Digital Trends

Perplexity AI turns into tutor with new language learning feature

What’s happened? Perplexity AI just dropped a new language learning feature built right into its platform. In a post shared on social media, the company announced a tool that helps users learn by ...