Min Woo Kang
서울대학교 협동과정 인공지능 전공 · 의학
Min Woo Kang 교수의 연구실은 신장질환, 특히 급성 신부전과 만성 신부전의 예측 및 관리에 초점을 맞춘 임상 기반의 데이터 기반 연구를 수행하고 있습니다. 특히 연속형 신장대체요법(CRRT) 투여 후 발생하는 저혈압 예측을 위해 머신러닝 알고리즘을 활용한 정밀의료 모델 개발에 주력하고 있으며, 신기능 이상 징후(예: 고요산혈증, 신세포 과혈류)와 신부전 진행 위험 요인의 규명에도 기여하고 있습니다. 연구는 임상적 실용성과 정확도 향상을 목표로 하며, 환자 중심의 개인화된 신장질환 관리 전략 수립을 추구합니다.
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
Machine learning algorithms increase the accuracy of mortality prediction for patients undergoing CRRT for acute kidney injury compared with previous scoring models.
Hypotension after starting continuous renal replacement therapy (CRRT) is associated with worse outcomes compared with normotension, but it is difficult to predict because several factors have interactive and complex effects on the risk. The present study applied machine learning algorithms to develop models to predict hypotension after initiating CRRT. Among 2349 adult patients who started CRRT due to acute kidney injury, 70% and 30% were randomly assigned into the training and testing sets, re
Hyperuricemia increases the risks of AKI and all-cause mortality in hospitalized patients.
Predicting the risk of end-stage renal disease (ESRD) progression facilitates appropriate nephrology care of patients with chronic kidney disease (CKD). Previously, the kidney failure risk equations (KFREs) were developed and validated in several cohorts. The purpose of this study is to validate the KFREs in a Korean population and to recalibrate the equations. A total of 38,905 adult patients, including 13,244 patients with CKD stages G3-G5, who were referred to nephrology were recruited. Using
Glomerular hyperfiltration may be associated with dementia. In this respect, subjects with glomerular hyperfiltration should be monitored more closely for signs and symptoms of dementia.
Abstract Background: Hypotension after starting continuous renal replacement therapy (CRRT) is associated with worse outcome, but it is difficult to predict because several factors have interactive and complex effects on the risk. The present study applied machine learning algorithms to develop models to predict hypotension after initiating CRRT. Methods: Among 2,349 adult patients who started CRRT due to acute kidney injury, 70% and 30% were randomly assigned into the training and testing sets,
In patients with chronic kidney disease (CKD), coronavirus disease 2019 (COVID-19) has a higher mortality rate than the general population; therefore, prevention is vital. To prevent COVID-19 infection, it is important to study individuals' risk aversion behavior. The objective of this study was to understand how the behavioral characteristics of physical distancing, hygiene practice, and exercise changed in patients with CKD during the COVID-19 pandemic and to identify the characteristics of pa
Purpose: To evaluate the severity of trauma, many scoring systems and predictive models have been presented. The quick Sequential Organ Failure Assessment (qSOFA) is a simple scoring system based on vital signs, and we expect it to be easier to apply to trauma patients than other trauma assessment tools. methods: This study was a cross-sectional study of trauma patients who visited the emergency department of Jeju National University Hospital. We excluded patients under the age of 18 years and u
This study provides population-scale evidence from general health screening participants, encouraging the prompt initiation of antihypertensive medication to reduce the risk of adverse outcomes. Delayed consideration of medication in primary health screenings may be associated with higher risks of MI, stroke, and death.
Patients with positive blood cultures in the intensive care unit (ICU) are at high risk for septic acute kidney injury requiring continuous kidney replacement therapy (CKRT), especially when treated with vancomycin. This study developed a machine learning model to predict CKRT and examined vancomycin's impact using deep learning-based causal inference. We analyzed ICU patients with positive blood cultures, utilizing the Medical Information Mart for Intensive Care III data set. The primary outcom