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 ...

Companies like Apple and Qualcomm are in the early stages of making on-device AI more useful. Amid all that, the 14-person ...

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 ...

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.

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 = ...

Background: Alterations in brain structure have been suggested to be associated with bulimia nervosa (BN). This study aimed to employ machine learning (ML) methods based on diffusion tensor imaging ...

1 School of Taxation and Public Administration, Shanghai Lixin University of Accounting and Finance, Shanghai, China. 2 School of Business, Computing and Social Sciences, University of Gloucestershire ...

A five-stage machine learning pipeline with integrated data transformation and feature selection strategies was presented in Khan and Zubair (2022) for automated classification of AD using Mini-Mental ...