Interpretable machine learning model for new-onset atrial fibrillation prediction in critically ill patients: a multi-center study

Topics

New-onset atrial fibrillation · New-onset atrial fibrillation · critically ill patients · Intensive care unit · Intensive care unit · machine learning · XGBoost · LASSO regression · MIMIC-IV database · MIMIC-III · SHapley Additive exPlanations · SHapley Additive exPlanations · mechanical ventilation · sepsis · blood urea nitrogen · continuous renal replacement therapy · urine output · percutaneous arterial oxygen saturation · interpretable prediction model · external validation

Share

Share on X

Cite this ranking

Pepkio Research Index (PRI). Topics and Trends in Most Cited Atrial Fibrillation Management and Outcomes Papers, Class of 2026. https://pri.pepkio.com/top-papers/atrial-fibrillation-management-and-outcomes/2026. Accessed 2026-08-20.

Methodology
Zheng Su, Tinsley Li, Thematic Shifts in Early-High-Impact Cancer Genomics and Diagnostics Research: A Bibliometric and Semantic Analysis. bioRxiv 2026.07.04.736459; doi: https://doi.org/10.64898/2026.07.04.736459