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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.

This work incorporates the Digital Imaging Communications in Medicine (DICOM) Standard into the Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) to standardize and accurately represent imaging studies, such as acquisition parameters, in multimodal research studies.

Real-world data (RWD) analyses primarily rely on structured clinical documentation collected through routine clinical care or driven by medical billing requirements. Patient-reported outcome measures (PROMs), integrated into electronic health records (EHRs), are an additional data source that could offer valuable insights into a patient's perspective and contribute to a more comprehensive understanding of health outcomes in RWD studies. This study aims to characterize agreement between PROMs symptoms and structured clinical [...]

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.

Artificial intelligence (AI) scribes may reduce documentation burden and improve clinician experience through generative AI automatically producing provider note sections from recordings of patient-provider encounters.

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.

To develop a locally deployed DeepSeek-powered closed-loop system for electronic nursing documentation quality control (QC) and evaluate its clinical efficacy through a multidimensional validation framework.

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.

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.

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