首页|Data on Machine Learning Described by Researchers at Chiba University Graduate S chool of Medicine (Machine learning algorithm for predicting 30-day mortality in patients receiving rapid response system activation: A retrospective nationwide ...)
Data on Machine Learning Described by Researchers at Chiba University Graduate S chool of Medicine (Machine learning algorithm for predicting 30-day mortality in patients receiving rapid response system activation: A retrospective nationwide ...)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-New research on artificial intelligence is the su bject of a new report. According to news reporting out of Chiba, Japan, by NewsR x editors, research stated, "This study investigated the accuracy of a machine l earning algorithm for predicting mortality in patients receiving rapid response system (RRS) activation." Our news reporters obtained a quote from the research from Chiba University Grad uate School of Medicine: "This retrospective cohort study used data from the In- Hospital Emergency Registry in Japan, which collects nationwide data on patients receiving RRS activation. The missing values in the dataset were replaced using multiple imputations (mode imputation, BayseRidge sklearn. linear model, and K- nearest neighbor model), and the enrolled patients were randomly assigned to the training and test cohorts. We established prediction models for 30-day mortalit y using the following four types of machine learning classifiers: Light Gradient Boosting Machine (LightGBM), eXtreme Gradient Boosting, random forest, and neur al network. Fifty-two variables (patient characteristics, details of RRS activat ion, reasons for RRS initiation, and hospital capacity) were used to construct t he prediction algorithm. The primary outcome was the accuracy of the prediction model for 30-day mortality. Overall, the data from 4,997 patients across 34 hosp itals were analyzed."
Chiba University Graduate School of Medi cineChibaJapanAsiaAlgorithmsCyborgsEmerging TechnologiesHospitalsMachine Learning
NETL
NSTL
