Fuzhou University Reports Findings in Machine Learning (Vancomycin trough concen tration in adult patients with periprosthetic joint infection: A machine learnin g-based covariate model)
Fuzhou University Reports Findings in Machine Learning (Vancomycin trough concen tration in adult patients with periprosthetic joint infection: A machine learnin g-based covariate model)
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning is th e subject of a report. According to news reporting originating from Fuzhou, Peop le's Republic of China, by NewsRx correspondents, research stated, "Although the re are various model-based approaches to individualized vancomycin (VCM) adminis tration, few have been reported for adult patients with periprosthetic joint inf ection (PJI). This work attempted to develop a machine learning (ML)-based model for predicting VCM trough concentration in adult PJI patients." Our news editors obtained a quote from the research from Fuzhou University, "The dataset of 287 VCM trough concentrations from 130 adult PJI patients was split into a training set (229) and a testing set (58) at a ratio of 8:2, and an indep endent external 32 concentrations were collected as a validation set. A total of 13 covariates and the target variable (VCM trough concentration) were included in the dataset. A covariate model was respectively constructed by support vector regression, random forest regression and gradient boosted regression trees and interpreted by SHapley Additive exPlanation (SHAP). The SHAP plots visualized th e weight of the covariates in the models, with estimated glomerular filtration r ate and VCM daily dose as the 2 most important factors, which were adopted for t he model construction. Random forest regression was the optimal ML algorithm wit h a relative accuracy of 82.8% and absolute accuracy of 67.2% (R =.61, mean absolute error = 2.4, mean square error = 10.1), and its predictio n performance was verified in the validation set. The proposed ML-based model ca n satisfactorily predict the VCM trough concentration in adult PJI patients."
Key words
Fuzhou/People's Republic of China/Asia/Antibiotics/Cyborgs/Emerging Technologies/Glycopeptides Therapy/Machine Le arning/Peptides/Vancomycin Therapy
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