Aberrant metabolism is the root cause of several serious health issues, creating a huge
burden to health and leading to diminished life expectancy. A dysregulated metabolism …

Background Racial bias is a key concern regarding the development, validation, and
implementation of machine learning (ML) models in clinical settings. Despite the potential of …

In this white paper, experts from the Digital Pathology Association (DPA) define terminology
and concepts in the emerging field of computational pathology, with a focus on its …

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 …

Abstract Machine learning (ML) holds great promise for impacting healthcare delivery;
however, to date most methods are tested in 'simulated'environments that cannot …

Retinal blood vessels provide information on the risk of cardiovascular disease (CVD). Here,
we report the development and validation of deep-learning models for the automated …

Purpose Due to the increasing demand for intensive care unit (ICU) treatment, and to
improve quality and efficiency of care, there is a need for adequate and efficient clinical …

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

With the advent of machine learning (ML) and deep learning (DL) empowered applications
for critical applications like healthcare, the questions about liability, trust, and interpretability …

Early detection of malign patterns in patients' biological signals can save millions of lives.
Despite the steady improvement of artificial intelligence–based techniques, the practical …