Objective Ontologies are widely used in the biomedical domain. While many tools exist for
the edition, alignment or evaluation of ontologies, few solutions have been proposed for …

A Bayesian network is a graphical model that uses probability theory to represent
relationships among its variables. The model is a directed acyclic graph whose nodes …

An individual's health and conditions are associated with a complex interplay between the
individual's genetics and his or her exposures to both internal and external environments …

Background The electronic health record (EHR) has become increasingly ubiquitous. At the
same time, health professionals have been turning to this resource for access to data that is …

Purpose The development of common ontologies has recently been identified as one of the
key challenges in the emerging field of surgical data science (SDS). However, past and …

Personalized medicine tailors treatments and dosages based on a patient's unique
characteristics, particularly its genetic profile. Over the decades, stratified research and …

Decision support systems, as means of disseminating clinical practice guidelines, are
powerful software that may lead to an improvement of medical practices. However, they are …

The main rationale of biomedical terminologies and formalized clinical information models is
to provide semantic standards to improve the exchange of meaningful clinical information …

Objective To improve semantic interoperability of electronic health records (EHRs) by
ontology-based mediation across syntactically heterogeneous representations of the same …

The advent of deep learning has engendered renewed and rapidly growing interest in
artificial intelligence (AI) in radiology to analyze images, manipulate textual reports, and plan …