Titlebook: Breath Analysis for Medical Applications; David Zhang,Dongmin Guo,Ke Yan Book 2017 Springer Nature Singapore Pte Ltd. 2017 Breath signal D

Accrue

Anticoagulants

cleaver

Improving the Transfer Ability of Prediction Modelseployment of e-noses, especially when the cost of sample collection is high. In this chapter, the transfer ability of prediction models is improved in two simple yet effective steps. First, windowed piecewise direct standardization (WPDS) is used to standardize the slave device, i.e., to transform t

Cognizance

glisten

A Transfer Learning Approach for Correcting Instrumental Variation and Time-Varying Driftmodel and correct these influential factors explicitly with the help of transfer samples. It generates drift-corrected and discriminative representation of the original data, which can then be applied to various prediction algorithms. Experimental results show that DCAE outperforms typical drift cor

付出

Drift Correction Using Maximum Independence Domain Adaptation unsupervised domain adaptation approaches. Maximum independence domain adaptation (MIDA) is proposed in this chapter for unsupervised drift correction. MIDA borrows the definition of domain features in the last chapter and learns features which have maximal independence with them, so as to reduce t

寬敞

惡心

Breath Sample Identification by Sparse Representation-Based Classification system in tandem with certain data evaluation algorithm offers an approach to analyze the compositions of breath. Currently, most algorithms rely on the generally designed pattern recognition techniques rather than considering the specific characteristics of data. They may not be suitable for odor

上腭

圓桶

Breath Signal Analysis for Diabeticse with abnormal concentrations and the concentrations rise gradually with patients’ blood glucose values. Therefore, the acetone in human breath can be used to monitor the development of diabetes. This chapter investigates the potential of breath signals analysis as a way for blood glucose monitorin