Prediction of postoperative morbidity after lung resection using an artificial neural network ensemble

Artificial Intelligence in Medicine

Volumn 30, Issue 1, 2004, Pages 61-69

  Santos García, Gustavo ^a   Varela, Gonzalo ^a   Novoa, Nuria ^a   Jiménez, Marcelo F ^a  

^a HOSPITAL UNIVERSITARIO DE SALAMANCA   (Spain)

Author keywords

Artificial neural network ensemble; Ensemble learning; Lung cancer; Lung resection; Predictive models; Risk adjusted morbidity

Indexed keywords

ARTIFICIAL INTELLIGENCE; BLOOD; MATHEMATICAL MODELS; NEURAL NETWORKS; PROBABILITY; PULMONARY DISEASES; TUMORS;

CHEST WALL; NON-SMALL CELL LUNG CANCERS (NSCLC);

MEDICINE;

ADULT; AGE DISTRIBUTION; AGED; ARTICLE; ARTIFICIAL NEURAL NETWORK; BLOOD TRANSFUSION; BODY MASS; CANCER CHEMOTHERAPY; CANCER STAGING; CONTROLLED STUDY; DATA ANALYSIS; DIABETES MELLITUS; FEMALE; FORCED EXPIRATORY VOLUME; HEART ARRHYTHMIA; HUMAN; ISCHEMIC HEART DISEASE; LUNG NON SMALL CELL CANCER; LUNG RESECTION; MAJOR CLINICAL STUDY; MALE; MEDICAL INFORMATION SYSTEM; MORBIDITY; OUTCOMES RESEARCH; PERIOPERATIVE PERIOD; POSTOPERATIVE COMPLICATION; PREDICTION; PREVALENCE; PRIORITY JOURNAL; PROBABILITY; PROSPECTIVE STUDY; SEX DIFFERENCE; STATISTICAL ANALYSIS; SURGICAL MORTALITY; SURGICAL RISK; THORAX SURGERY; VALIDATION PROCESS;

EID: 0346848887     PISSN: 09333657     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0933-3657(03)00059-9     Document Type: Article

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