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Our objective is to develop algorithms for encoding clinical text into representations that can be used for a variety of phenotyping tasks.

HIV infection risk can be estimated based on not only individual features but also social network information. However, there have been insufficient studies using n machine learning methods that can maximize the utility of such information. Leveraging a state-of-the-art network topology modeling method, graph convolutional networks (GCN), our main objective was to include network information for the task of detecting previously unknown HIV infections.

Clinical trials, prospective research studies on human participants carried out by a distributed team of clinical investigators, play a crucial role in the development of new treatments in health care. This is a complex and expensive process where investigators aim to enroll volunteers with predetermined characteristics, administer treatment(s), and collect safety and efficacy data. Therefore, choosing top-enrolling investigators is essential for efficient clinical trial execution and is 1 of the [...]

Although patient generated health data (PGHD) has stimulated excitement about its potential to increase patient engagement and to offer clinicians new insights into patient health status, we know little about these efforts at scale and whether they align with patient preferences. This study sought to characterize provider-led PGHD approaches, assess whether they aligned with patient preferences, and identify challenges to scale and impact.

The objective of this study is to characterize the dynamic structure of primary care consultations by identifying typical activities and their inter-relationships to inform the design of automated approaches to clinical documentation using natural language processing and summarization methods.

The purpose of this study was to determine if medication cost transparency alerts provided at time of prescribing led ambulatory prescribers to reduce their use of low-value medications.

The testing of informatics tools designed for use during mass casualty incidents presents a unique problem as there is no readily available population of victims or identical exposure setting. The purpose of this article is to describe the process of designing, planning, and executing a functional exercise to accomplish the research objective of validating an informatics tool specifically designed to identify and triage victims of irritant gas syndrome agents.

Electronic health records (EHRs) were expected to yield numerous benefits. However, early studies found mixed evidence of this. We sought to determine whether widespread adoption of modern EHRs in the US has improved clinical care.

The study sought to develop and evaluate an electronic health record-based child abuse clinical decision support system in 2 general emergency departments.