IEEE

Enhanced Anomaly Detection in Ethereum: Unveiling and Classifying Threats With Machine Learning

Abstract: Blockchain has emerged as a groundbreaking security technology, playing a vital role in various industries such as banking, the Internet of Things (IoT), healthcare, education, and voting.
IEEE

Machine Learning–Based Hypertension Risk Stratification Using Logistic Regression and XGBoost

Abstract: Hypertension is a critical global health concern, necessitating accurate prediction models and effective prescription decisions to mitigate its risks. This study proposes a hybrid machine ...

Understanding Homoskedasticity in Regression Modeling With Examples

Discover the importance of homoskedasticity in regression models, where error variance is constant, and explore examples that illustrate this key concept.
Open Heart

Artificial intelligence-based clustering to identify functional risk phenotypes in heart failure

Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...
Scientific Research Publishing

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

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