Publications by authors named "Seung Hee Lim"
Article Synopsis
- Sepsis is a leading cause of postoperative mortality, and conventional scoring systems have limited predictive accuracy; this study explores using machine-learning algorithms to enhance predictions for patients with sepsis from peritonitis.
- The research involved analyzing demographic and clinical data, focusing on indicators like the delta neutrophil index and various lab results, to assess mortality risk through multiple machine-learning models.
- The CatBoost model proved most effective, with an area under the curve of 0.933, highlighting factors like increased delta neutrophil index and septic shock as significant predictors of mortality in these patients.*
The objectives of this study were to analyze antioxidant activities and identify volatile compounds in mixed berry juice after fermentation by lactic acid bacteria (LAB). Antioxidant activity of the mixed berry juice increased significantly from 209.57±2.
View Article and Find Full Text PDFPurpose: Competency-based assessment helps to improve performance and to standardize education programs for hospice and palliative care professionals. This paper aims to report the process and results of developing the hospice and palliative care competencies by multidisciplinary experts in Korea.
Methods: The competency development task force team of Korean hospice and palliative care professionals was comprised of seven physicians, four nurses, two social workers, and two clergy.