A machine learning-based approach to prognostic analysis of thoracic transplantations

Artificial Intelligence in Medicine

Volumn 49, Issue 1, 2010, Pages 33-42

  Delen, Dursun ^a   Oztekin, Asil ^b,c   Kong, Zhenyu ^b  

^a OKLAHOMA STATE UNIVERSITY   (United States)

^b Oklahoma State University   (United States)

^c GEDIZ UNIVERSITY   (Turkey)

Author keywords

Data mining; Machine learning; Prognostic index; Survival analysis; Thoracic Transplantation; UNOS

Indexed keywords

ALLOCATION POLICIES; ARTIFICIAL NEURAL NETWORK; BEST FIT; COX REGRESSION; DATA MINING METHODS; DATA SETS; DOMAIN-SPECIFIC KNOWLEDGE; EFFECTIVE ANALYSIS; INTEGRATED MACHINES; K-MEANS CLUSTERING ALGORITHM; KAPLAN-MEIER; KERNEL FUNCTION; LARGE DATASETS; LINEAR MODELING; MACHINE LEARNING; MACHINE LEARNING METHODS; MEDICAL EXPERTS; MULTI LAYER PERCEPTRON; NON-LINEAR RELATIONSHIPS; OPTIMAL NUMBER; PREDICTIVE FACTORS; PREDICTIVE MODELS; PREDICTIVE VARIABLES; PREDICTOR VARIABLES; PROGNOSTIC ANALYSIS; RADIAL BASIS; REGRESSION TREE MODELS; RISK GROUPING; STATISTICAL ANALYSIS; SURVIVAL ANALYSIS; SURVIVAL MODEL; SURVIVAL TIME;

BIOINFORMATICS; BIOLOGICAL ORGANS; CLUSTER ANALYSIS; CLUSTERING ALGORITHMS; DATA MINING; GROUP TECHNOLOGY; LEARNING ALGORITHMS; LEARNING SYSTEMS; METAL RECOVERY; MINING; NEURAL NETWORKS; OPTIMIZATION; REGRESSION ANALYSIS; SENSITIVITY ANALYSIS; TRANSPLANTATION (SURGICAL); TREES (MATHEMATICS);

TIME DOMAIN ANALYSIS;

ARTICLE; ARTIFICIAL NEURAL NETWORK; CLUSTER ANALYSIS; CONTROLLED STUDY; DATA EXTRACTION; GRAFT RECIPIENT; HEART LUNG TRANSPLANTATION; HIGH RISK PATIENT; HUMAN; INTERMETHOD COMPARISON; KAPLAN MEIER METHOD; KERNEL METHOD; KNOWLEDGE BASE; MACHINE LEARNING; MEDICAL EXPERT; PATIENT IDENTIFICATION; PREDICTION; PREDICTOR VARIABLE; PRIORITY JOURNAL; PROGNOSIS; PROPORTIONAL HAZARDS MODEL; SENSITIVITY ANALYSIS; SUPPORT VECTOR MACHINE; SURVIVAL TIME; VALIDATION PROCESS;

DATA MINING; DATABASES, FACTUAL; FEMALE; HUMANS; KAPLAN-MEIERS ESTIMATE; LUNG TRANSPLANTATION; MALE; MEDICAL INFORMATICS APPLICATIONS; MODELS, BIOLOGICAL; PROGNOSIS;

EID: 77951625860     PISSN: 09333657     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.artmed.2010.01.002     Document Type: Article

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