Exploratory study to identify radiomics classifiers for lung cancer histology

Frontiers in Oncology

Volumn 6, Issue MAR, 2016, Pages

  Wu, Weimiao ^a,b   Parmar, Chintan ^a,c   Grossmann, Patrick ^a,d   Quackenbush, John ^b,d   Lambin, Philippe ^c   Bussink, Johan ^e   Mak, Raymond ^a   Aerts, Hugo J W L ^a,d  

^a BRIGHAM AND WOMEN S HOSPITAL   (United States)

^b HARVARD SCHOOL OF PUBLIC HEALTH   (United States)

^c MAASTRICHT UNIVERSITY   (Netherlands)

^d DANA FARBER CANCER INSTITUTE   (United States)

^e RADBOUD UNIVERSITY MEDICAL CENTER   (Netherlands)

Author keywords

Computational science; Feature selection; Lung cancer histology; Quantitative imaging; Radiomics

Indexed keywords

ADULT; AGED; AREA UNDER THE CURVE; ARTICLE; COMPUTER ASSISTED TOMOGRAPHY; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; HIGH THROUGHPUT SCREENING; HISTOLOGY; HUMAN; K NEAREST NEIGHBOR; LUNG CANCER; MAJOR CLINICAL STUDY; MATHEMATICAL MODEL; NON SMALL CELL LUNG CANCER; POSITRON EMISSION TOMOGRAPHY; RADIOMICS; RECEIVER OPERATING CHARACTERISTIC; SCORING SYSTEM; UNIVARIATE ANALYSIS;

EID: 84964417455     PISSN: None     EISSN: 2234943X     Source Type: Journal    
DOI: 10.3389/fonc.2016.00071     Document Type: Article

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