The use of digital twins (DTs) has proliferated across various fields and industries, with a
recent surge in the healthcare sector. The concept of digital twin for health (DT4H) holds …

Radiomics is the quantitative analysis of standard‐of‑care medical imaging; the information
obtained can be applied within clinical decision support systems to create diagnostic …

Deep learning methods have achieved significant results in various fields. Due to the
success of these methods, many researchers have used deep learning algorithms in …

Alzheimer's disease (AD) is characterized by non-linear, genetic-driven pathophysiological
dynamics with high heterogeneity in biological alterations and disease spatial-temporal …

Brain imaging genomics is an emerging data science field, where integrated analysis of
brain imaging and genomics data, often combined with other biomarker, clinical, and …

The early detection of lung cancer is attained with the detection of initial stage nodules (3−
30 mm) which can exorbitantly increase the 5-year survival rate of lung cancer patients …

Pathology is the medical specialty concerned with the study of the disease nature and
causes, playing a key role in bridging basic researches and clinical medicine. In the course …

The heterogeneous and high-dimensional nature of omics data presents various challenges
in gaining insights while analysis. In the era of big data, omics data is available as genome …

Pancreatic cystic lesions (PCLs) are well-known precursors of pancreatic cancer. Their
diagnosis can be challenging as their behavior varies from benign to malignant disease …

Oncological diseases account for a significant portion of the burden on public healthcare
systems with associated costs driven primarily by complex and long-lasting therapies …