The building sector accounts for 36% of the total global energy usage and 40% of
associated Carbon Dioxide emissions. Therefore, the forecasting of building energy …

The adoption of machine learning (ML) and, more specifically, deep learning (DL)
applications into all major areas of our lives is underway. The development of trustworthy AI …

This paper reviews literature on data-driven approaches for characterizing rock mass and
ground conditions in tunnels. There have been significant advances in the use of both …

Abstract Extracellular Vesicles (EVs), particularly exosomes, recently exploded into
nanomedicine as an emerging drug delivery approach due to their superior biocompatibility …

The term robustness is ubiquitous in modern Machine Learning (ML). However, its meaning
varies depending on context and community. Researchers either focus on narrow technical …

Objective Despite recent calls for home healthcare (HHC) to integrate informatics, the
application of machine learning in HHC is relatively unknown. Thus, this study aimed to …

The world energy consumption has increased by+ 195% since 1970 with more than 80% of
the energy mix originating from fossil fuels, thus leading to pollution and global warming …

Digital radiography is one of the most common and cost-effective standards for the diagnosis
of bone fractures. For such diagnoses expert intervention is required which is time …

Retinopathy is an eye disease caused by diabetes, and early detection and treatment can
potentially reduce the risk of blindness in diabetic retinopathy sufferers. Using retinal Fundus …

Identifying in situ hazardous materials can improve demolition waste recyclability and
reduce project uncertainties concerning cost overrun and delay. With the attempt to …