Biomolecule-based nanostructures are inherently multifunctional and harbour diverse
biological activities, which can be explored for cancer nanomedicine. The supramolecular …

Objective To summarize how artificial intelligence (AI) is being applied in COVID-19
research and determine whether these AI applications integrated heterogenous data from …

Multi-modal medical image segmentation is a crucial task in oncology that enables the
precise localization and quantification of tumors. The aim of this work is to present a meta …

Chronic liver diseases, resulting from chronic injuries of various causes, lead to cirrhosis
with life-threatening complications including liver failure, portal hypertension, hepatocellular …

Objective To distinguish benign from malignant cystic renal lesions (CRL) using a contrast-
enhanced CT-based radiomics model and a clinical decision algorithm. Methods This dual …

The increasing availability of molecular data provided by next-generation sequencing (NGS)
techniques is allowing improvement in the possibilities of diagnosis and prognosis in renal …

Radiology in Canada is advancing through innovations in clinical practices and research
methodologies. Recent developments focus on refining evidence-based practice guidelines …

In recent years, advancements in medical treatment and imaging technologies have
revolutionized the assessment of tumor response. However, the Response Evaluation …

Breast ultrasound has emerged as a valuable imaging modality in the detection and
characterization of breast lesions, particularly in women with dense breast tissue or …

In vivo multi-modal bioimaging technology has a high reputation for providing more
comprehensive/accurate information and analysis, especially in cancer diagnosis and …