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Acute Kidney Injury

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Comparison of machine learning and logistic regression models in predicting acute kidney injury: A systematic review and meta-analysis.

International journal of medical informatics
INTRODUCTION: We aimed to assess whether machine learning models are superior at predicting acute kidney injury (AKI) compared to logistic regression (LR), a conventional prediction model.

A deep-learning model to continuously predict severe acute kidney injury based on urine output changes in critically ill patients.

Journal of nephrology
BACKGROUND: Acute Kidney Injury (AKI), a frequent complication of pateints in the Intensive Care Unit (ICU), is associated with a high mortality rate. Early prediction of AKI is essential in order to trigger the use of preventive care actions.

Comparison of plasma neutrophil gelatinase-associated lipocalin (NGAL) levels after robot-assisted laparoscopic and retropubic radical prostatectomy: an observational study.

Brazilian journal of anesthesiology (Elsevier)
BACKGROUND AND OBJECTIVES: Patients undergoing radical prostatectomy are at increased risk of Acute Kidney Injury (AKI) because of intraoperative bleeding, obstructive uropathy, and older age. Neutrophil Gelatinase-Associated Lipocalin (NGAL) may bec...

Artificial Intelligence in Hypertension: Seeing Through a Glass Darkly.

Circulation research
Hypertension remains the largest modifiable cause of mortality worldwide despite the availability of effective medications and sustained research efforts over the past 100 years. Hypertension requires transformative solutions that can help reduce the...

Selective Suturing or Sutureless Technique in Robot-assisted Partial Nephrectomy: Results from a Propensity-score Matched Analysis.

European urology focus
BACKGROUND: Despite efforts aimed at preserving renal function, the functional decline after robot-assisted partial nephrectomy (RAPN) is not negligible. To address the risk of intraparenchymal vessel injuries during renorrhaphy, with consequent loss...

Optimizing predictive strategies for acute kidney injury after major vascular surgery.

Surgery
BACKGROUND: Postoperative acute kidney injury is common after major vascular surgery and is associated with increased morbidity, mortality, and cost. High-performance risk stratification using a machine learning model can inform strategies that mitig...

Assessment of acute kidney injury risk using a machine-learning guided generalized structural equation model: a cohort study.

BMC nephrology
BACKGROUND: Acute kidney injury is common in the surgical intensive care unit (ICU). It is associated with poor patient outcomes and high healthcare resource usage. This study's primary objective is to help identify which ICU patients are at high ris...

Prediction of outcomes after acute kidney injury in hospitalised patients: protocol for a systematic review.

BMJ open
INTRODUCTION: Acute kidney injury (AKI) is common and is associated with negative long-term outcomes. Given the heterogeneity of the syndrome, the ability to predict outcomes of AKI may be beneficial towards effectively using resources and personalis...

Cross-site transportability of an explainable artificial intelligence model for acute kidney injury prediction.

Nature communications
Artificial intelligence (AI) has demonstrated promise in predicting acute kidney injury (AKI), however, clinical adoption of these models requires interpretability and transportability. Non-interoperable data across hospitals is a major barrier to mo...

Machine Learning to Predict Mortality and Critical Events in a Cohort of Patients With COVID-19 in New York City: Model Development and Validation.

Journal of medical Internet research
BACKGROUND: COVID-19 has infected millions of people worldwide and is responsible for several hundred thousand fatalities. The COVID-19 pandemic has necessitated thoughtful resource allocation and early identification of high-risk patients. However, ...