换一批Evaluation of electrohysterogram measured from different gestational weeks for recognizing preterm delivery: a preliminary study using random Forest.
第一作者：
Jin,Peng
第一单位：
College of Life Science and Bioengineering, Beijing University of Technology, Intelligent Physiological Measurement and Clinical Translation, Beijing International Platform for Scientific and Technological Cooperation, Beijing, China.
作者：
关键词
ACC, accuracyADASYN, adaptive synthetic sampling approachANN, artificial neural networkAR, auto-regressive modelAUC, the area under the curveCorrDim, correlation dimensionDT, decision treeEHG, electrohysterogramElectrohysterogram (EHG)Feature extractionGestational weekIUPC, intrauterine pressure catheterK-NN, K-nearestLDA, linear discriminant analysisLE, Lyapunov exponentMDF, median frequencyMNF, mean frequencyPE, preterm delivery before the 26th week of gestationPF, peak frequencyPL, preterm delivery after the 26th week of gestationPreterm deliveryQDA, quadratic discriminant analysisRF, random forestRMS, root mean squareROC, the receiver operating characteristic curveRandom forest (RF).SD, standard deviationSE, energy values in signalSM, maximum values in signalSS, singular values in signalSV, variance values in signalSVM, support vector machineSampEn, sample entropyTE, term delivery before the 26th week of gestationTL, term delivery after the 26th week of gestationTOCO, tocodynamometerTPEHG, term-preterm electrohysterogramTr, time reversibilityτz, zero-crossing
DOI
10.1016/j.bbe.2019.12.003
PMID
32308250
发布时间
2020-09-28
- 浏览5
Biocybernetics and biomedical engineering
352-362页
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