Abstract Explainable Artificial Intelligence (XAI) is an emerging research topic of machine
learning aimed at unboxing how AI systems' black-box choices are made. This research field …

Artificial intelligence (AI) models are increasingly finding applications in the field of
medicine. Concerns have been raised about the explainability of the decisions that are …

Radiomic features have a wide range of clinical applications, but variability due to image
acquisition factors can affect their performance. The harmonization tool ComBat is a …

Artificial intelligence, which has been actively applied in a broad range of industries in
recent years, is an active area of interest for many researchers. Dentistry is no exception to …

Radiomics is a rapidly developing field of research focused on the extraction of quantitative
features from medical images, thus converting these digital images into minable, high …

Breast magnetic resonance imaging (MRI) is the most sensitive imaging modality for breast
cancer diagnosis and is widely used clinically. Dynamic contrast-enhanced MRI is the basis …

Artificial intelligence (AI) has seen dramatic growth over the past decade, evolving from a
niche super specialty computer application into a powerful tool which has revolutionized …

Radiomics is the method of choice for investigating the association between cancer imaging
phenotype, cancer genotype and clinical outcome prediction in the era of precision …

Simple Summary The two most common cross-sectional imaging modalities, computed
tomography (CT) and magnetic resonance imaging (MRI), have shown enormous utility in …

Existing quantitative imaging biomarkers (QIBs) are associated with known biological tissue
characteristics and follow a well-understood path of technical, biological and clinical …