Data‐driven epoch, the development of machine learning (ML) in materials and device
design is an irreversible trend. Its ability and efficiency to handle nonlinear and game …

The reliability of any quantitative structure–activity relationship (QSAR) model depends on
multiple aspects such as the accuracy of the input dataset, selection of significant …

Cross-validation is one of the most widely used data resampling methods for model
selection and evaluation. Cross-validation can be used to tune the hyperparameters of …

Artificial intelligence (AI) is being increasingly used to automate and improve technologies
within the field of medical imaging. A critical step in the development of an AI algorithm is …

Intelligent algorithms can empower the development of smart manufacturing, since they can
provide optimal solutions for detection, analysis, prediction and optimization. In recent ten …

The vitamin D receptor is highly expressed in the gastrointestinal tract where it transacts
gene expression. With current limited understanding of the interactions between the gut …

Background and objectives Parkinson's Disease (PD) is a devastating chronic neurological
condition. Machine learning (ML) techniques have been used in the early prediction of PD …

Abstract The Internet of Medical Things (IoMT) facilitates patients with all-time-connected
medical devices through cost-effective solutions and a feeling of comfort with round-the …

Formative feedback has long been recognised as an effective tool for student learning, and
researchers have investigated the subject for decades. However, the actual implementation …

Petroleum and natural gas resources (PNGR) are some of the major forms of fossil energy
that are important for the development of industry and energy security. Along with the …