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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.

This study aims to compare the diagnostic abilities of humans in wound image assessment with those of an AI-based model, examine how "expertise" affects clinicians' diagnostic performance, and investigate the heterogeneity in clinical judgments.

This review paper comprehensively summarizes healthcare provider (HCP) evaluation of explanations produced by explainable artificial intelligence methods to support point-of-care, patient-specific, clinical decision-making (CDM) within medical settings. It highlights the critical need to incorporate human-centered (HCP) evaluation approaches based on their CDM needs, processes, and goals.

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.

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 However, as preprint articles are not peer-reviewed before publication, their quality varies significantly, posing challenges for evidence inclusion in systematic reviews.

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.

Drug interaction checking software is ubiquitous in clinical decision support systems (CDSS-DI) but patient relevance and accuracy are variable and the impact on patient outcomes is unproven. We compared the effectiveness of CDSS-DI with similar care without CDSS-DI.