Automated machine learning (AutoML) is recognized for its efficiency in facilitating model
development due to its ability to perform tasks autonomously, without constant human …

Automatic analysis of medical images using machine learning techniques has gained
significant importance over the years. A large number of approaches have been proposed …

Introduction Automated machine learning (autoML) removes technical and technological
barriers to building artificial intelligence models. We aimed to summarise the clinical …

With most technical fields, there exists a delay between fundamental academic research and
practical industrial uptake. Whilst some sciences have robust and well-established …

Background and Aim: Many studies associated with the combination of machine learning
(ML) and pharmacometrics have appeared in recent years. ML can be used as an initial step …

Cervical cancer is the most common cancer and ranked as 4th in morbidity and mortality
among Malaysian women. Currently, Magnetic Resonance Imaging (MRI) is considered as …

Objective Invasive lung adenocarcinoma (ILA) with micropapillary (MPP)/solid (SOL)
components has a poor prognosis. Preoperative identification is essential for decision …

Purpose To determine if an explainable artificial intelligence (XAI) model enhances the
accuracy and transparency of predicting embryo ploidy status based on embryonic …

Weather forecasting plays a vital role in numerous sectors, but accurately capturing the
complex dynamics of weather systems remains a challenge for traditional statistical models …

Radiomics is the process of extracting useful quantitative features of high-dimensional data
that allows for automated disease classification, including atherosclerotic disease. Hence …