Objective To examine the accuracy of artificial intelligence (AI) for the detection of breast
cancer in mammography screening practice. Design Systematic review of test accuracy …

Artificial intelligence (AI) has the potential to transform every facet of cardiovascular practice
and research. The exponential rise in technology powered by AI is defining new frontiers in …

Clinical prediction models follow a standard development pipeline: model development and
internal validation; external validation; and clinical impact studies. External validation …

Since their invention in the early 2000s, tyrosine kinase inhibitors (TKIs) have gained
prominence as the most effective pathway-directed anti-cancer agents. TKIs have shown …

Background Clinical prediction models are often not evaluated properly in specific settings
or updated, for instance, with information from new markers. These key steps are needed …

Objective Although the role of artificial intelligence (AI) in medicine is increasingly studied,
most patients do not benefit because the majority of AI models remain in the testing and …

Artificial intelligence (AI) has experienced explosive growth in oncology and related
specialties in recent years. The improved expertise in data capture, the increased capacity …

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

Predicting future outcomes of patients is essential to clinical practice, with many prediction
models published each year. Empirical evidence suggests that published studies often have …

Aims To study the impact of genotype on the performance of the 2019 risk model for
arrhythmogenic right ventricular cardiomyopathy (ARVC). Methods and results The study …