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Rheumatic heart disease (RHD) affects an estimated 39 million people worldwide and is the most common acquired heart disease in children and young adults. Echocardiograms are the gold standard for diagnosis of RHD, but there is a shortage of skilled experts to allow widespread screenings for early detection and prevention of the disease progress. We propose an automated RHD diagnosis system that can help bridge this gap.

To propose an algorithm that utilizes only timestamps of longitudinal electronic health record data to classify clinical deterioration events.

Despite broad electronic health record (EHR) adoption in U.S. hospitals, there is concern that an "advanced use" digital divide exists between critical access hospitals (CAHs) and non-CAHs. We measured EHR adoption and advanced use over time to analyzed changes in the divide.

PubMed has suffered from the author ambiguity problem for many years. Existing studies on author name disambiguation (AND) for PubMed only used internal metadata for development. However, some of them are incomplete (eg, a large number of names are only abbreviated and their full names are not available) or less discriminative. To this end, we present a new disambiguation method, namely AggAND, by aggregating information from external databases.

Most nonfederal acute care hospitals use electronic health records (EHRs) certified by the Office of the National Coordinator for Health Information Technology. In 2015, the Office of the National Coordinator for Health Information Technology finalized the 2015 Health IT Certification Edition and adoption by hospitals began in 2016. We examine the impact of the 2015 Edition on rates of interoperable exchange among nonfederal acute hospitals.

The study sought to develop and evaluate neural natural language processing (NLP) packages for the syntactic analysis and named entity recognition of biomedical and clinical English text.

To summarize how artificial intelligence (AI) is being applied in COVID-19 research and determine whether these AI applications integrated heterogenous data from different sources for modeling.

The COVID-19 pandemic has once again highlighted the ubiquity and persistence of health inequities along with our inability to respond to them in a timely and effective manner. There is an opportunity to address the limitations of our current approaches through new models of informatics-enabled research and clinical practice that shift the norm from small- to large-scale patient engagement. We propose augmenting our approach to address health inequities through informatics-enabled [...]

As master of science in health informatics (MSc HI) programs emerge in developing countries, quality assurance of these programs is essential. This article describes a comprehensive comparative analysis of competencies covered by accredited MSc HI programs in the East African common labor and educational zone.

To assess the frequency, fidelity, and impact of replication studies in the clinical decision support system (CDSS) literature.