Background Interest in the application of machine learning (ML) to the design, conduct, and
analysis of clinical trials has grown, but the evidence base for such applications has not …

The use of artificial intelligence, and the deep-learning subtype in particular, has been
enabled by the use of labeled big data, along with markedly enhanced computing power …

We propose a novel method for imputing missing data by adapting the well-known
Generative Adversarial Nets (GAN) framework. Accordingly, we call our method Generative …

Objective To conduct a systematic scoping review of explainable artificial intelligence (XAI)
models that use real-world electronic health record data, categorize these techniques …

Solid-organ transplantation is a life-saving treatment for end-stage organ disease in highly
selected patients. Alongside the tremendous progress in the last several decades, new …

The advent of big data brings with it data with more and more dimensions and thus a
growing need to be able to efficiently select which features to use for a variety of problems …

Kidney transplantation is a critical treatment option for end-stage kidney disease patients,
offering improved quality of life and increased survival rates. However, the complexities of …

Objectives: This survey analyses the latest literature contributions to clinical decision support
systems (DSSs) on a two-year period (2017-2018), focusing on the approaches that adopt …

The proposed donor heart selection guidelines provide evidence-based and expert-
consensus recommendations for the selection of donor hearts following brain death. These …

Background Machine learning (ML) is increasingly used in research for subtype definition
and risk prediction, particularly in cardiovascular diseases. No existing ML models are …