Introduction Artificial Intelligence (AI) enables computers to perform tasks that normally require human intelligence- such as learning from data, recognizing ...

Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...

Read more about AI-driven air quality system promises faster, more reliable urban health warnings on Devdiscourse ...

6G visions include immersive extended reality, holographic communications, tactile internet applications, and large-scale digital twins. Supporting these services will demand fully autonomous network ...

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...

Researchers at the University of California, Santa Cruz have trained lab-grown brain organoids to solve a goal-directed task, ...

Market valued at $1.68B in 2024, projected to reach $4.58B by 2033 at 13.4% CAGR, driven by chronic wound prevalence ...

One example involved a system built by a summer intern for his own project work. The tool geolocates devices within a drawing set and links them to a digital twin of the facility. Instead of searching ...

Abstract: This study presents a comprehensive benchmarking of 33 machine learning (ML) algorithms for bearing fault classification using vibration data, with a focus on real-world deployment in ...

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

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 = ...