Lancet Digit Health
January 2025
Background: Patient notes contain substantial information but are difficult for computers to analyse due to their unstructured format. Large-language models (LLMs), such as Generative Pre-trained Transformer 4 (GPT-4), have changed our ability to process text, but we do not know how effectively they handle medical notes. We aimed to assess the ability of GPT-4 to answer predefined questions after reading medical notes in three different languages.
View Article and Find Full Text PDFBackground: The aim of this study was to document the incidence, spectrum and outcomes of Second Primary Malignancy (SPM) in a prospectively followed-up population of Head and Neck Squamous carcinoma (HNSCC) patients accrued in six prospective trials and treated with definitive radiotherapy.
Materials And Methods: Patients were prospectively followed up over time and data on SPM collected after IRB approval after establishing the diagnosis of SPM based on clinical criteria. Descriptive statistics to determine clinic demographic characteristics and spectrum of SPM encountered, time to event outcomes (SPM-DFS - Disease-free survival after diagnosis of second primary, SPM-OS - Overall survival after diagnosis of second primary) and univariate analysis of factors of likely prognostic significance were performed.
Introduction: Genomics is a lifespan competency that is important for improving health outcomes for individuals, families, and communities. Nurses play a key role in genomic healthcare and realizing the potential of the genomic era.
Methods: We aimed to chart the current state of genomics in nursing by conducting a systematic scoping review of the literature in four databases (2012-2022).