An international research team, with significant involvement from the Medical University of Vienna, has developed a new AI-based analysis method that can accurately classify brain tumors using genetic ...

Researchers used 16S rRNA sequencing and machine learning to identify gut microbiome patterns associated with insulin resistance severity in people with type 2 diabetes. XGBoost models showed that ...

Researchers from the Department of Computer Science at Bar-Ilan University and from NVIDIA's AI research center in Israel ...

High school students gain PhD-led mentorship, publish original research, and build real-world AI models through ...

A recent review concluded that artificial intelligence (AI) is rapidly transforming the diagnosis and treatment of haematological malignancies by enhancing diagnostic accuracy and ...

Researchers claim that leading image editing AIs can be jailbroken through rasterized text and visual cues, allowing prohibited edits to bypass safety filters and succeed in up to 80.9% of cases.

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...

A new low-power sensor node framework combines sensing and machine learning, with the potential to enhance real-time environmental monitoring while optimizing energy efficiency.

Introduction: The unmanned aerial vehicle -based light detection and ranging (UAV-LiDAR) can quickly acquire the three-dimensional information of large areas of vegetation, and has been widely used in ...

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...