This scoping review of 70 studies found that AI is used mainly to detect and measure health-related stigma, rather than to ...

Abstract: Traditional machine learning (ML) techniques have limitations that make it difficult for existing algorithms to diagnose cervical cancer. These limitations include lower accuracy and an ...

Researchers from Stony Brook University, in collaboration with Ecosuite and Ecogy Energy, have developed a self-supervised machine-learning algorithm designed to identify physical anomalies in solar ...

Artificial intelligence (AI) could help biopharmaceutical manufacturers detect contamination in cell cultures sooner than conventional approaches, thereby helping to reduce waste and batch losses. The ...

*Artificial intelligence is rapidly transforming how doctors identify disease, with cancer diagnostics at the forefront of this medical revolution. For millions of patients, AI now provides a crucial ...

A new study applying multi-omics techniques and machine learning identified 33 plasma proteins that differ significantly in patients with amyotrophic lateral sclerosis (ALS). The findings suggest ALS ...

This project detects digits using CNNs and OpenCV. It includes image preprocessing, model training on MNIST, real-time detection, and evaluation with accuracy metrics. Built with Python, ...

Abstract: One of the main causes of cancer-related deaths is lung cancer, and increasing survival rates requires early detection. The use of sophisticated machine learning (ML) algorithms to improve ...

A decrease in processing speed is associated with several antecedents, including old age, a decline in fine motor function, and the deterioration of brain connectivity. Patient processing speed is a ...

Division of Applied Chemistry, Faculty of Engineering, Hokkaido University, Kita 13, Nishi 8, Kita-ku, Sapporo, Hokkaido 060-8628, Japan ...