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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 [...]

Clinical notes present a wealth of information for applications in the clinical domain, but heterogeneity across clinical institutions and settings presents challenges for their processing. The clinical natural language processing field has made strides in overcoming domain heterogeneity, while pretrained deep learning models present opportunities to transfer knowledge from one task to another. Pretrained models have performed well when transferred to new tasks; however, it is not well understood if [...]

The goals of this study are to describe the value and impact of Project HealthDesign (PHD), a program of the Robert Wood Johnson Foundation that applied design thinking to personal health records, and to explore the applicability of the PHD model to another challenging translational informatics problem: the integration of AI into the healthcare system.

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

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.

Although social and environmental factors are central to provider-patient interactions, the data that reflect these factors can be incomplete, vague, and subjective. We sought to create a conceptual framework to describe and classify data about presence, the domain of interpersonal connection in medicine.