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Risk prediction models are used in hospitals to identify pediatric patients at risk of clinical deterioration, enabling timely interventions and rescue. The objective of this study was to develop a new explainer algorithm that uses a patient's clinical notes to generate text-based explanations for risk prediction alerts.

This paper presents the results from a competition challenging participants to develop entity linking models using a subset of annotated MIMIC-IV-Note data and the SNOMED CT Terminology.

Clinicians retrieve data from electronic health record (EHR) systems and summarize them into clinical information to accomplish clinical reasoning and decision-making tasks. Visualization, using meaningful summarization methods and intuitive presentation approaches, can enhance this process. This systematic review examines how EHR data are summarized, visualized, and aligned with the 7 clinical reasoning and decision-making tasks shared by clinicians.

Family data are a valuable data source in bioinformatic research. This is because family members often share common genetic and environmental exposures. Collecting this family data is traditionally very labor intensive but advances in electronic health record (EHR) data mining has proven useful when identifying pedigrees linked to longitudinal health histories. These are called e-pedigrees. Unfortunately, e-pedigrees tend to miss the oldest patients who inherently have the longest and richest [...]

Evaluate the association between telemedicine intensity and ambulatory physician electronic health record (EHR) use following the COVID-19 pandemic.

To explore the performance of 4 large language model (LLM) chatbots for the analysis of 2 of the most commonly used tools for the advanced analysis of systematic reviews (SRs) and meta-analyses.

Recommendation systems have emerged as prevalent and effective tools. Investigating the impact of recommendation algorithms on users' health information adoption behavior can aid in optimizing health information services and advancing the construction and development of online health community platforms.

Systematic reviews in comparative effectiveness research require timely evidence synthesis. With the rapid advancement of medical research, preprint articles play an increasingly important role in accelerating knowledge dissemination. However, as preprint articles are not peer-reviewed before publication, their quality varies significantly, posing challenges for evidence inclusion in systematic reviews.

Infections following healthcare-associated interventions drive patient morbidity and mortality, making early detection essential. Traditional predictive models utilize preoperative surgical characteristics. This study evaluated whether integrating postoperative laboratory values and their kinetics could improve outcome prediction.

Missed diagnosis of genetic conditions is a persistent challenge in clinical care, particularly for familial hypercholesterolemia (FH), hereditary breast and ovarian cancer (HBOC), and Lynch syndrome-conditions designated by the U.S. Centers for Disease Control and Prevention (CDC) as Tier 1 genomic applications. This scoping review summarizes evidence on the use of electronic health record (EHR)-based algorithms to identify individuals with these conditions.