Bioinformatics methods for learning radiation-induced lung inflammation from heterogeneous retrospective and prospective data

Journal of Biomedicine and Biotechnology

Volumn 2009, Issue , 2009, Pages

  El Naqa, Issam ^a   Spencer, Sarah J ^a   Almiron Bonnin, Damian ^b   Deasy, Joseph O ^a   Bradley, Jeffrey D ^a  

^a WASHINGTON UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b EARLHAM COLLEGE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL MARKER;

ARTICLE; BIOINFORMATICS; CANCER RADIOTHERAPY; CONTROLLED STUDY; DATA MINING; HUMAN; KERNEL METHOD; LUNG CANCER; LUNG INJURY; MACHINE LEARNING; PROTEIN EXPRESSION; PROTEOMICS; RADIATION PNEUMONIA; SERUM; SUPPORT VECTOR MACHINE; BIOLOGICAL MODEL; BIOLOGY; LUNG NON SMALL CELL CANCER; LUNG TUMOR; METABOLISM; METHODOLOGY; PRINCIPAL COMPONENT ANALYSIS; PROSPECTIVE STUDY; RADIATION RESPONSE; RADIOTHERAPY; RETROSPECTIVE STUDY;

CARCINOMA, NON-SMALL-CELL LUNG; COMPUTATIONAL BIOLOGY; DOSE-RESPONSE RELATIONSHIP, RADIATION; HUMANS; LUNG NEOPLASMS; MODELS, BIOLOGICAL; PRINCIPAL COMPONENT ANALYSIS; PROSPECTIVE STUDIES; PROTEOMICS; RADIATION PNEUMONITIS; RADIOTHERAPY; RETROSPECTIVE STUDIES;

EID: 67650898266     PISSN: 11107243     EISSN: 11107251     Source Type: Journal    
DOI: 10.1155/2009/892863     Document Type: Article

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