Electronic health record (EHR) data must be mapped to standard information models for interoperability and to support research across organizations. New information models are being developed and validated for data important to nursing, but a signifi...
BACKGROUND: Clinical information is often stored as free text, e.g. in discharge summaries or pathology reports. These documents are semi-structured using section headers, numbered lists, items and classification strings. However, it is still challen...
Manually annotated clinical corpora are commonly used as the gold standards for the training and evaluation of clinical natural language processing (NLP) tools. The creation of these manual annotation corpora, however, is both costly and time-consumi...
Journal of the American Medical Informatics Association : JAMIA
29635469
OBJECTIVE: In recent years, electronic health record systems have been widely implemented in China, making clinical data available electronically. However, little effort has been devoted to making drug information exchangeable among these systems. Th...
Journal of the American Medical Informatics Association : JAMIA
30137378
OBJECTIVE: Standards such as the Logical Observation Identifiers Names and Codes (LOINC®) are critical for interoperability and integrating data into common data models, but are inconsistently used. Without consistent mapping to standards, clinical d...
This paper describes a novel technique for annotating logical forms and answers for clinical questions by utilizing Fast Healthcare Interoperability Resources (FHIR). Such annotations are widely used in building the semantic parsing models (which aim...
The FHIR specification provides a mechanism to access clinical terminologies using a standard API, and many existing terminologies, such as SNOMED CT, are well supported. However, in areas such as genomics, terminologies from other domains are starti...
While natural language processing (NLP) of unstructured clinical narratives holds the potential for patient care and clinical research, portability of NLP approaches across multiple sites remains a major challenge. This study investigated the portabi...
BACKGROUND AND OBJECTIVE: To take full advantage of decision support, machine learning, and patient-level prediction models, it is important that models are not only created, but also deployed in a clinical setting. The KETOS platform demonstrated in...
Due to continuous evolution of biomedical data, biomedical ontologies are becoming larger and more complex, which leads to the existence of many overlapping information. To support semantic inter-operability between ontology-based biomedical systems,...