Several machine learning models have been proposed to predict vancomycin (VCM)-associated nephrotoxicity; however, they have notable limitations. Specifically, they do not use the area under the concentration-time curve (AUC) as recommended in the la...
INTRODUCTION: Machine learning (ML) has been tried in predicting outcomes following sepsis. This study aims to identify the utility of stacked ensemble algorithm in predicting mortality.
Computer methods and programs in biomedicine
39626503
INTRODUCTION: Prostate cancer remains a significant health concern, with radical prostatectomy being a common treatment approach. However, predicting postoperative functional outcomes, particularly urinary continence and erectile function, poses chal...
European journal of clinical pharmacology
39570408
OBJECTIVE: Limited sampling strategies are widely employed in clinical practice to minimize the number of blood samples required for the accurate area under the curve calculations, as obtaining these samples can be costly and challenging. Traditional...
The Journal of international medical research
39668733
OBJECTIVE: This systematic review aimed to provide a comprehensive overview of the application of machine learning (ML) in predicting multiple adverse drug events (ADEs) using electronic health record (EHR) data.
European journal of clinical investigation
39660499
BACKGROUND: Although oral anticoagulation decreases the risk of thromboembolism in patients with atrial fibrillation (AF), a residual risk of thrombotic events still exists. This study aimed to construct machine learning (ML) models to predict the re...
OBJECTIVE: To develop a supervised machine learning model to predict the occurrence and intensity of tooth sensitivity (TS) in patients undergoing in-office dental bleaching testing various algorithm models.
BACKGROUND: While deep learning classifiers have shown remarkable results in detecting chest X-ray (CXR) pathologies, their adoption in clinical settings is often hampered by the lack of transparency. To bridge this gap, this study introduces the neu...
Medical science monitor : international medical journal of experimental and clinical research
39623707
BACKGROUND Predicting 24-hour intraocular pressure (IOP) fluctuations is crucial for enhancing glaucoma management. Traditional methods of measuring 24-hour IOP fluctuations are complex and present certain limitations. The present study leverages mac...
OBJECTIVE: This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy, considering factors such as data heterogeneity,...