Semi-supervised analysis of human brain tumours from partially labeled MRS information, using manifold learning models

International Journal of Neural Systems

Volumn 21, Issue 1, 2011, Pages 17-29

  Cruz Barbosa, Raúl ^a   Vellido, Alfredo ^b  

^a UNIVERSIDAD TECNOLÓGICA DE LA MIXTECA   (Mexico)

^b UNIVERSITAT POLITÈCNICA DE CATALUNYA   (Spain)

Author keywords

human brain tumours; manifold learning; Semi supervised learning; unlabeled MRS information

Indexed keywords

BRAIN TUMOURS; DATA MODELING; GENERATIVE TOPOGRAPHIC MAPPING; HUMAN BRAIN; LAPLACIAN EIGENMAPS; MANIFOLD LEARNING; MEDICAL DECISION SUPPORTS; MEDICAL DIAGNOSIS; NEURO-ONCOLOGY; OUTCOME PREDICTION; SEMI-SUPERVISED; SEMI-SUPERVISED LEARNING; UNLABELED MRS INFORMATION;

BRAIN; DECISION SUPPORT SYSTEMS; DIAGNOSIS; ONCOLOGY; SUPERVISED LEARNING; TUMORS;

BRAIN MODELS;

ARTICLE; ARTIFICIAL INTELLIGENCE; BRAIN TUMOR; COMPUTER ASSISTED DIAGNOSIS; DECISION SUPPORT SYSTEM; GLIOBLASTOMA; HUMAN; METHODOLOGY; NONLINEAR SYSTEM; NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY;

ARTIFICIAL INTELLIGENCE; BRAIN NEOPLASMS; DECISION SUPPORT TECHNIQUES; DIAGNOSIS, COMPUTER-ASSISTED; GLIOBLASTOMA; HUMANS; MAGNETIC RESONANCE SPECTROSCOPY; NONLINEAR DYNAMICS;

EID: 78751551710     PISSN: 01290657     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0129065711002626     Document Type: Conference Paper

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