For centuries, humans have sought to classify diseases based on phenotypic presentation
and available treatments. Today, a wide landscape of strategies, resources, and tools exist …

Simple Summary Cancer is a complex phenomenon and cancer research is increasingly
data-rich. Representing this knowledge in a manner that is both human and computer …

Background Assessment of functional ability, including activities of daily living (ADLs), is a
manual process completed by skilled health professionals. In the presented research, an …

Electronic medical records (EMR) contain key information about the different symptomatic
episodes that a patient went through. They carry a great potential in order to improve the …

Cancer remains one of the most challenging diseases to treat in the medical field. Machine
learning has enabled in-depth analysis of rich multi-omics profiles and medical imaging for …

Purpose The purpose of this study is to examine the state of research into adoption of
machine learning systems within the health sector, to identify themes that have been studied …

The amalgamation of artificial intelligence (AI) and machine learning (ML) in healthcare
offers a revolutionary prospect to improve patient outcomes, optimize workflow, and curtail …

Background Unstructured text created by patients represents a rich, but relatively
inaccessible resource for advancing patient-centered care. This study aimed to develop an …

Background Artificial intelligence methods applied to electronic medical records (EMRs)
hold the potential to help physicians save time by sharpening their analysis and decisions …

Ontologies and AI develop into two movements for space express information extraction
effectively used in information‐based frameworks. Ontologies are a postponed outcome of …