Survival analysis of patients with high-grade gliomas based on data mining of imaging variables

American Journal of Neuroradiology

Volumn 33, Issue 6, 2012, Pages 1065-1071

  Zacharaki, Evangelia I ^a,b   Morita, N ^a   Bhatt, P ^a   O'Rourke, D M ^a   Melhem, E R ^a   Davatzikos, C ^a  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

^b UNIVERSITY OF PATRAS   (Greece)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY; ADULT; AGED; ARTICLE; BRAIN BLOOD FLOW; CANCER PROGNOSIS; DATA MINING; DIFFUSION TENSOR IMAGING; GLIOBLASTOMA; GLIOMA; GLIOSARCOMA; HISTOPATHOLOGY; HUMAN; MAJOR CLINICAL STUDY; OUTCOME ASSESSMENT; PREDICTION; SURVIVAL RATE;

ADULT; AGED; AGED, 80 AND OVER; ALGORITHMS; ARTIFICIAL INTELLIGENCE; BRAIN NEOPLASMS; DATA MINING; DATABASES, FACTUAL; DECISION SUPPORT SYSTEMS, CLINICAL; FEMALE; GLIOMA; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MALE; MIDDLE AGED; PATTERN RECOGNITION, AUTOMATED; PENNSYLVANIA; PREVALENCE; PROPORTIONAL HAZARDS MODELS; REPRODUCIBILITY OF RESULTS; RISK FACTORS; SENSITIVITY AND SPECIFICITY; SURVIVAL ANALYSIS; SURVIVAL RATE;

EID: 84862508110     PISSN: 01956108     EISSN: 1936959X     Source Type: Journal    
DOI: 10.3174/ajnr.A2939     Document Type: Article

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