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Long-term breast cancer survivors (BCS) constitute a complex group of patients, whose number is estimated to continue rising, such that, a dedicated long-term clinical follow-up is necessary.

The study aims to assess racial and language disparities in pediatric emergency department (ED) triage using analytical techniques and provide insights into the extent and nature of the disparities in the ED setting.

Despite federally mandated collection of sex and gender demographics in the electronic health record (EHR), longitudinal assessments are lacking. We assessed sex and gender demographic field utilization using EHR metadata.

To report on clinical informatics (CI) fellows' job search and early careers.

The increasing demands for curated, high-quality research data are driving the emergence of a novel registry type. The need to assemble, curate, and export this data grows, and the conventional simplicity of registry models is driving the need for advanced, multimodal data registries-the dawn of the next-generation registry.

To develop and evaluate a data-driven process to generate suggestions for improving alert criteria using explainable artificial intelligence (XAI) approaches.

Question answering (QA) systems have the potential to improve the quality of clinical care by providing health professionals with the latest and most relevant evidence. However, QA systems have not been widely adopted. This systematic review aims to characterize current medical QA systems, assess their suitability for healthcare, and identify areas of improvement.

Stressful life events, such as going through divorce, can have an important impact on human health. However, there are challenges in capturing these events in electronic health records (EHR). We conducted a scoping review aimed to answer 2 major questions: how stressful life events are documented in EHR and how they are utilized in research and clinical care.

We conducted an implementation planning process during the pilot phase of a pragmatic trial, which tests an intervention guided by artificial intelligence (AI) analytics sourced from noninvasive monitoring data in heart failure patients (LINK-HF2).