Genotype imputation is crucial for GWAS, but reference panels and existing benchmarking studies prioritize European individuals. Consequently, it is unclear which publicly available reference panel should be used for Pakistani individuals, and whether ancestry composition or sample size of the panel matters more for imputation accuracy. Our study compared different reference panels to impute genotype data in 1814 Pakistani individuals, finding the best performance balancing accuracy and coverage with meta-imputation with TOPMed and the expanded 1000 Genomes (ex1KG) reference.
View Article and Find Full Text PDFImportance: Classification of persons with long COVID (LC) or post-COVID-19 condition must encompass the complexity and heterogeneity of the condition. Iterative refinement of the classification index for research is needed to incorporate newly available data as the field rapidly evolves.
Objective: To update the 2023 research index for adults with LC using additional participant data from the Researching COVID to Enhance Recovery (RECOVER-Adult) study and an expanded symptom list based on input from patient communities.
Background: Large language models (LLMs) have shown promise in various professional fields, including medicine and law. However, their performance in highly specialized tasks, such as extracting ICD-10-CM codes from patient notes, remains underexplored.
Objective: The primary objective was to evaluate and compare the performance of ICD-10-CM code extraction by different LLMs with that of human coder.
Importance: Medical ethics is inherently complex, shaped by a broad spectrum of opinions, experiences, and cultural perspectives. The integration of large language models (LLMs) in healthcare is new and requires an understanding of their consistent adherence to ethical standards.
Objective: To compare the agreement rates in answering questions based on ethically ambiguous situations between three frontier LLMs (GPT-4, Gemini-pro-1.