Latest AI and machine learning research in information technology for healthcare professionals.
UNLABELLED: The Immune Epitope Database (IEDB) project incorporates independently developed ontologies and controlled vocabularies into its curation and search interface. This simplifies curation practices, improves the user query experience and facilitates interoperability between the IEDB and other resources. While the use of independently developed ontologies has long been recommended as a best...
Clinical care and research data are widely dispersed in isolated systems based on heterogeneous data models. Biomedicine predominantly makes use of connected datasets based on the Semantic Web paradigm. Initiatives like Bio2RDF created Resource Description Framework (RDF) versions of Omics resources, enabling sophisticated Linked Data applications. In contrast, electronic healthcare records (EHR) ...
Electronic Health Records (EHRs) are now being massively used in hospitals what has motivated current developments of new methods to process clinical ...
"A solid ontology-based analysis with a rigorous formal mapping for correctness" is one of the ten reasons why the HL7 standard Fast Healthcare Intero...
Because of recent replacement of physical documents with electronic medical records (EMR), the importance of information processing in the medical fie...
Opioid dependence and overdose is on the rise. One indicator is the increasing trends of prescription buprenorphine use among patient on chronic pain ...
In healthcare, applying deep learning models to electronic health records (EHRs) has drawn considerable attention. This sequential nature of EHR data ...
The infobuttons allows the solving of information needs. In our study, the use of Infobuttons is described, analyzing the number of queries to UpToDat...
Disease ontology, defined as a causal chain of abnormal states, is believed to be a valuable knowledge base in medical information systems. Automatic ...
Automatic encoding of diagnosis and procedures can increase the interoperability and efficacy of the clinical cooperation. The concept, rule-based and...
Identifying important predicative indicators for prognosis is useful since these factors help for understanding diseases and determining treatments fo...
Association rule mining has received significant attention from both the data mining and machine learning communities. While data mining researchers f...
The analysis of lung sounds, collected through auscultation, is a fundamental component of pulmonary disease diagnostics for primary care and general ...
Deep learning has achieved remarkable results in the areas of computer vision, speech recognition, natural language processing and most recently, even...
Nowadays, text classification and text mining of Electronic Medical Record (EMR) have become the basis of the Big Data research in biomedical fields. ...
Medicomp Point of Care Clinical Knowledgebase, MEDCIN is designed to support integrated care documentation and the care planning functions of nurses a...
To estimate the prevalence of problem opioid use, we used natural language processing (NLP) techniques to identify clinical notes containing text indi...
OBJECTIVE: The limitations of the DSM nosology for capturing dimensionality and overlap in psychiatric syndromes, and its poor correspondence to under...
Diabetes Mellitus (DM) affects hundreds of millions of people worldwide and it imposes a large economic burden on healthcare systems. We present a web...
Patient Safety (PS) standardization is the key to improve interoperability and expand international share of incident reporting system knowledge. By a...