Exa-scale volumes of medical data have been produced for decades. In most cases, the
diagnosis is reported in free text, encoding medical knowledge that is still largely …

Background The narrative free-text data in electronic medical records (EMRs) contain
valuable clinical information for analysis and research to inform better patient care …

Background The constant growth of biomedical data is accompanied by the need for new
methodologies to effectively and efficiently extract machine-readable knowledge for training …

Computational pathology can significantly benefit from ontologies to standardize the
employed nomenclature and help with knowledge extraction processes for high-quality …

Introduction Hospitals generate large amounts of data and this data is generally modeled
and labeled in a proprietary way, hampering its exchange and integration. Manually …

Abstract Information Retrieval (IR) is a discipline deeply rooted on evaluation that in many
cases relies on annotated data as ground truth. Manual annotation is a demanding and time …

In the realm of Machine Learning and Deep Learning, there is a need for high-quality
annotated data to train and evaluate supervised models. An extensive number of annotation …

Health information systems (HIS) play a fundamental role in society, providing a solid
technological basis for collecting, storing, processing, and making decisions in the …

With Electronic Medical Records (EMRs) being widely adopted in hospitals around the
world, they accelerate the transition of documenting patient-related data from paperbased to …

Large volumes of medical data have been produced for decades. These data include
diagnoses, which are often reported as free text, thus encoding medical knowledge that is …