Yuan Wu

Summary

Affiliation: University of California
Country: USA

Publications

  1. pmc Grid Binary LOgistic REgression (GLORE): building shared models without sharing data
    Yuan Wu
    Division of Biomedical Informatics, Department of Medicine, University of California San Diego, La Jolla, California 92093, USA
    J Am Med Inform Assoc 19:758-64. 2012
  2. pmc WebGLORE: a web service for Grid LOgistic REgression
    Wenchao Jiang
    Division of Biomedical Informatics, University of California, San Diego, La Jolla, CA 92093, USA and Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
    Bioinformatics 29:3238-40. 2013
  3. pmc EXpectation Propagation LOgistic REgRession (EXPLORER): distributed privacy-preserving online model learning
    Shuang Wang
    Division of Biomedical Informatics, University of California, San Diego, La Jolla, San Diego, CA 92093 0728, USA
    J Biomed Inform 46:480-96. 2013
  4. pmc Selecting cases for whom additional tests can improve prognostication
    Xiaoqian Jiang
    Division of Biomedical Informatics, Department of Medicine University of California at San Diego, La Jolla, CA 92093, USA
    AMIA Annu Symp Proc 2012:1260-8. 2012
  5. pmc Preserving Institutional Privacy in Distributed binary Logistic Regression
    Yuan Wu
    Division of Biomedical Informatics, Department of Medicine University of California San Diego, La Jolla 92093, USA
    AMIA Annu Symp Proc 2012:1450-8. 2012
  6. pmc I-spline Smoothing for Calibrating Predictive Models
    Yuan Wu
    Division of Biomedical Informatics, University of California at San Diego, La Jolla, California 92093
    AMIA Summits Transl Sci Proc 2012:39-46. 2012

Collaborators

Detail Information

Publications6

  1. pmc Grid Binary LOgistic REgression (GLORE): building shared models without sharing data
    Yuan Wu
    Division of Biomedical Informatics, Department of Medicine, University of California San Diego, La Jolla, California 92093, USA
    J Am Med Inform Assoc 19:758-64. 2012
    ....
  2. pmc WebGLORE: a web service for Grid LOgistic REgression
    Wenchao Jiang
    Division of Biomedical Informatics, University of California, San Diego, La Jolla, CA 92093, USA and Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
    Bioinformatics 29:3238-40. 2013
    ..WebGLORE seamlessly integrates AJAX, JAVA Applet/Servlet and PHP technologies to provide an easy-to-use web service for biomedical researchers to break down policy barriers during information exchange...
  3. pmc EXpectation Propagation LOgistic REgRession (EXPLORER): distributed privacy-preserving online model learning
    Shuang Wang
    Division of Biomedical Informatics, University of California, San Diego, La Jolla, San Diego, CA 92093 0728, USA
    J Biomed Inform 46:480-96. 2013
    ..The proposed EXPLORER supports asynchronized communication, which relieves the participants from coordinating with one another, and prevents service breakdown from the absence of participants or interrupted communications...
  4. pmc Selecting cases for whom additional tests can improve prognostication
    Xiaoqian Jiang
    Division of Biomedical Informatics, Department of Medicine University of California at San Diego, La Jolla, CA 92093, USA
    AMIA Annu Symp Proc 2012:1260-8. 2012
    ..The same is not true for some other groups...
  5. pmc Preserving Institutional Privacy in Distributed binary Logistic Regression
    Yuan Wu
    Division of Biomedical Informatics, Department of Medicine University of California San Diego, La Jolla 92093, USA
    AMIA Annu Symp Proc 2012:1450-8. 2012
    ..We tested our method using both simulated and clinical data, showing how it is possible to protect the privacy of individuals and of institutions using a distributed strategy...
  6. pmc I-spline Smoothing for Calibrating Predictive Models
    Yuan Wu
    Division of Biomedical Informatics, University of California at San Diego, La Jolla, California 92093
    AMIA Summits Transl Sci Proc 2012:39-46. 2012
    ..e.,1.6x, 1.4x, and 1.4x on the three datasets compared to the average of competitors-Binning, Platt Scaling, Isotonic Regression, Monotone Spline Smoothing, Smooth Isotonic Regression) without deterioration of discrimination...