Outlier detection and removal improves accuracy of machine learning approach to multispectral burn diagnostic imaging-Reference-Cited by-同舟云学术

Outlier detection and removal improves accuracy of machine learning approach to multispectral burn diagnostic imaging

Published:2015-08-25 Issue:12 Volume:20 Page:121305
ISSN:1083-3668
Container-title:Journal of Biomedical Optics
language:en
Short-container-title:J. Biomed. Opt

Author:

Li Weizhi¹,Mo Weirong¹,Zhang Xu¹,Squiers John J.²,Lu Yang¹,Sellke Eric W.¹,Fan Wensheng¹,DiMaio J. Michael²,Thatcher Jeffrey E.¹

Affiliation:

1. Spectral MD, Inc., 2515 McKinney Avenue, Suite 1000, Dallas, Texas 75201, United States

2. Spectral MD, Inc., 2515 McKinney Avenue, Suite 1000, Dallas, Texas 75201, United StatesbBaylor Research Institute, 3310 Live Oak, Suite 501, Dallas, Texas 75204, United States

Publisher

SPIE-Intl Soc Optical Eng

Subject

Biomedical Engineering,Atomic and Molecular Physics, and Optics,Biomaterials,Electronic, Optical and Magnetic Materials

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5. Light-tissue interactions;Valery,2003

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