Application of the Naïve Bayesian Classifier to optimize treatment decisions

Radiotherapy and Oncology

Volumn 86, Issue 2, 2008, Pages 211-216

  Kazmierska, Joanna ^a   Malicki, Julian ^a  

^a Great Poland Cancer Centre   (Poland)

Author keywords

Artificial Intelligence; Brain tumours; Education; Na ve Bayesian Classifier; Radiotherapy

Indexed keywords

ACCURACY; ARTICLE; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; BRAIN TUMOR; CANCER GROWTH; CANCER PATIENT; CANCER RADIOTHERAPY; CANCER RELAPSE; CANCER RISK; CLINICAL DECISION MAKING; CLINICAL EVALUATION; COMPARATIVE STUDY; CONTROLLED STUDY; DISEASE COURSE; GLIOBLASTOMA; HIGH RISK PATIENT; HUMAN; MAJOR CLINICAL STUDY; MENINGIOMA; NAIVE BAYESIAN CLASSIFIER; PRIORITY JOURNAL; PROBABILITY; QUALITY CONTROL; RISK ASSESSMENT; SENSITIVITY AND SPECIFICITY; VALIDATION STUDY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; BRAIN NEOPLASMS; DECISION MAKING; DISEASE PROGRESSION; HUMANS; NEOPLASM RECURRENCE, LOCAL; RETROSPECTIVE STUDIES; RISK ASSESSMENT; SENSITIVITY AND SPECIFICITY;

EID: 38949131864     PISSN: 01678140     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.radonc.2007.10.019     Document Type: Article

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