윤수빈 교수

Acute kidney injury (AKI) after liver transplantation has been reported to be associated with increased mortality. Recently, machine learning approaches were reported to have better predictive ability than the classic statistical analysis. We compared the performance of machine learning approaches with that of logistic regression analysis to predict AKI after liver transplantation. We reviewed 1211 patients and preoperative and intraoperative anesthesia and surgery-related variables were obtaine

In modern anesthesia, multiple medical devices are used simultaneously to comprehensively monitor real-time vital signs to optimize patient care and improve surgical outcomes. However, interpreting the dynamic changes of time-series biosignals and their correlations is a difficult task even for experienced anesthesiologists. Recent advanced machine learning technologies have shown promising results in biosignal analysis, however, research and development in this area is relatively slow due to th

Predicting in-hospital cardiac arrest in patients admitted to an intensive care unit (ICU) allows prompt interventions to improve patient outcomes. We developed and validated a machine learning-based real-time model for in-hospital cardiac arrest predictions using electrocardiogram (ECG)-based heart rate variability (HRV) measures. The HRV measures, including time/frequency domains and nonlinear measures, were calculated from 5 min epochs of ECG signals from ICU patients. A light gradient boosti

Clostridium difficile infection (CDI) is one of the most common nosocomial infections. Dysbiosis of the gut microbiota due to consumption of antibiotics is a major contributor to CDI. Recently, fecal microbiota transplantation (FMT) has been applied to treat CDI. However, FMT has important limitations including uncontrolled exposure to pathogens and standardization issues. Therefore, it is necessary to evaluate alternative treatment methods, such as bacteriotherapy, as well as the mechanism thro

Bispectral index (BIS), a useful marker of anaesthetic depth, is calculated by a statistical multivariate model using nonlinear functions of electroencephalography-based subparameters. However, only a portion of the proprietary algorithm has been identified. We investigated the BIS algorithm using clinical big data and machine learning techniques. Retrospective data from 5,427 patients who underwent BIS monitoring during general anaesthesia were used, of which 80% and 20% were used as training d

For pheochromocytoma and sympathetic paraganglioma (PPGL), surgery can be used as a curative treatment; however, the life-threatening risk of perioperative hemodynamic instability (HI) presents challenges. This study aimed to analyze the incidence and predictive factors of perioperative HI. The electronic medical records of 114 consecutive patients who underwent surgery for PPGLs at our institution were retrospectively reviewed. HI was defined as one or more episodes of systolic blood pressure >

Online monitoring of titanium dissolution during operation to understand the degradation pathway of the porous transport layer in water electrolyzers.

Titrating tacrolimus concentration in liver transplantation recipients remains a challenge in the early post-transplant period. This multicenter retrospective cohort study aimed to develop and validate a machine-learning algorithm to predict tacrolimus concentration. Data from 443 patients undergoing liver transplantation between 2017 and 2020 at an academic hospital in South Korea were collected to train machine-learning models. Long short-term memory (LSTM) and gradient-boosted regression tree

Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely.

Healing chronic diabetic wounds is challenging because of excessive reactive oxygen species (ROS) and hypoxia in the wound microenvironment. To address this issue, we propose a hydrogel wound dressing composed of polyethylene glycol (PEG) cross-linked with a biomimetic catalase, Fe-containing porphyrin (FeP) (i.e., FeP hydrogel). The immobilized FeP can serve as a catalyst for both ROS scavenging and O₂ generation. The properties of the hydrogels were optimized by varying the composit

The commercialization of proton exchange membrane water electrolysis (PEMWE) for green hydrogen production hinges on the development of low-cost, high-performance titanium porous transport layers (PTLs). This study introduces a triple-layer Ti-PTL with a graded porous structure and a 75% ultra-high porosity backing layer, fabricated through tape casting and roll calendering. This triple-layer PTL, composed of a microporous layer, an interlayer, and a highly porous backing layer, enhances catalys

The widespread use of remifentanil during total intravenous anesthesia (TIVA) has raised concerns about the risk of postoperative remifentanil-associated pain. Although a recent meta-analysis suggests that remifentanil-associated pain is unlikely to occur in patients with TIVA because of the protective effect of co-administered propofol, the evidence is not conclusive. We retrospectively assessed 635 patients who received robotic thyroid surgery under TIVA to evaluate the risk of remifentanil-as