Intracranial pressure level prediction in traumatic brain injury by extracting features from multiple sources and using machine learning methods

Proceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010

Volumn , Issue , 2010, Pages 510-515

  Chen, Wenan ^a   Cockrell, Charles ^b   Ward, Kevin R ^c   Najarian, Kayvan ^a  

^a Virginia Commonwealth University   (United States)

^b VIRGINIA COMMONWEALTH UNIVERSITY   (United States)

^c VIRGINIA COMMONWEALTH UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

Classification; Intracranial pressure prediction; Nested cross validation; Texture analysis

Indexed keywords

10-FOLD CROSS-VALIDATION; CLASSIFICATION; CLASSIFICATION RESULTS; CROSS VALIDATION; CT SLICES; DEMOGRAPHIC INFORMATION; EXTRACTING FEATURES; FEATURE SELECTION; INJURY SEVERITY; INTRACRANIAL PRESSURE; INTRACRANIAL PRESSURE PREDICTION; MACHINE LEARNING METHODS; MULTIPLE SOURCE; NESTED CROSS VALIDATION; NON-INTRUSIVE METHOD; OVERFITTING; PARAMETER SELECTION; PREDICTION MODEL; SHIFT MEASUREMENT; TEXTURE ANALYSIS; TEXTURE FEATURES; TRAINING DATA; TRAUMATIC BRAIN INJURIES;

BIOINFORMATICS; BRAIN; FORECASTING; LEARNING SYSTEMS; MATHEMATICAL MODELS; TEXTURES;

FEATURE EXTRACTION;

EID: 79952364810     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/BIBM.2010.5706619     Document Type: Conference Paper

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