Health informatics class gets an AI makeover to better prepare nursing students

From navigating electronic health records and HIPAA compliance to applying predictive analytics, health informatics is now essential to the daily work of nursing. But aligning coursework with that ...
IEEE

Dynamic Machine Learning Framework for Secure, Ultra-Reliable, and Energy-Efficient Open RAN Systems

Abstract: This paper proposes a machine learning (ML)-driven framework for Open Radio Access Networks (ORAN) to address security, Ultra-Reliable Low-Latency Communication (URLLC), and energy ...
IEEE

A Novel Relative Density and Nonmembership-Based Intuitionistic Fuzzy Twin SVM for Class Imbalance Learning

Abstract: A major challenge in machine learning is the accurate categorization of data in the presence of noise, outliers, and imbalanced class distributions. Fuzzy support vector machines and their ...
TMCnet

CompuChild Expands Its Suite of Artificial Intelligence and Machine Learning Classes for Children

DUBLIN, Calif., Jan. 16, 2026 /PRNewswire/ -- CompuChild, a children's education franchise business dedicated to offering after-school enrichment programs across the United States and Canada, today ...
Scientific Research Publishing

Diabetes Diagnosis Using Machine Learning: A SVM-Based Approach ()

1 Faculty of Mathematics and Computer Science,, Felix Houphouët-Boigny University, Abidjan, Côte d’Ivoire. 2 Institute for Mathematical Research (IRMA), Abidjan, Côte d’Ivoire. 3 Higher Teacher ...
Frontiers

A comparative analysis of binary and multi-class classification machine learning algorithms to detect current frailty status using the English longitudinal study of ageing (ELSA)

Physical frailty is a pressing public health issue that significantly increases the risk of disability, hospitalization, and mortality. Early and accurate detection of frailty is essential for timely ...
GitHub

Lung Cancer Prediction Project

In this project, we leverage the power of artificial intelligence in healthcare to predict lung cancer risks. By employing various machine learning techniques, we aim to assist medical professionals ...
Scientific Research Publishing

Erfani, S.M., Rajasegarar, S., Karunasekera, S. and Leckie, C. (2016) High-Dimensional and Large-Scale Anomaly Detection Using a Linear One-Class SVM with Deep Learning ...

ABSTRACT: Industrial appearance anomaly detection (AD) focuses on accurately identifying and locating abnormal regions in images. However, due to issues such as scarce abnormal samples, complex ...