A network of actual physical objects or “IoT components” linked to the internet and equipped
with sensors, electronics, software, and network connectivity is known as the Internet of …

The aim of this informative review was to investigate the application of radiomics in cancer
imaging and to summarize the results of recent studies to support oncological imaging with …

Learning from imbalanced datasets is a nontrivial task for supervised learning community.
Traditional classifiers may have difficulties to learn the concept related to the minority class …

Lung adenocarcinoma (LUAD), a prevalent histological type of lung cancer and a subtype of
non-small cell lung cancer (NSCLC) accounts for 45–55% of all lung cancer cases. Various …

Background Gout prediction is essential for the development of individualized prevention
and treatment plans. Our objective was to develop an efficient and interpretable machine …

Objective Data imbalance is a pervasive issue in medical data mining, often leading to
biased and unreliable predictive models. This study aims to address the urgent need for …

Early recognition of risk factors for prolonged mechanical ventilation (PMV) could allow for
early clinical interventions, prevention of secondary complications such as nosocomial …

Imbalanced classification is a major issue that degrades the performance of conventional
classifiers in machine learning. As a result, predecessors have proposed methods to …

In their study, Stavropoulos et al.(2023) capitalized on supervised machine learning and a
longitudinal design and reported that the User-Avatar Bond could be accurately employed to …

The development of electronic health records (EHR) systems has enabled the collection of a
vast amount of digitized patient data. However, utilizing EHR data for predictive modeling …