title: Models for diagnosing chest pain: is CART helpful?
abstract: The use of classification and regression tree (CART) methodology is explored for the diagnosis of patients complaining of anterior chest pain. The results are compared with those previously obtained using correspondence analysis and independent Bayes classification. The technique is shown to be of potential value for identifying important indicators and cutpoints for continuous variables, although the overall classification performance was rather disappointing. Suggestions are made for extensions to the methodology to make it more suitable for clinical practice.
authors.affiliation: Royal College of Nursing Institute, London, U.K.
authors.forename: N J
authors.initials: NJ
authors.lastname: Crichton
authors.forename: J P
authors.initials: JP
authors.lastname: Hinde
authors.forename: J
authors.initials: J
authors.lastname: Marchini
mesh_terms: D000367:Age Factors; D001499:Bayes Theorem; D002637:Chest Pain / Q000145:classification* / Q000175:diagnosis* / Q000209:etiology; D003663:Decision Trees; D006331:Heart Diseases / Q000150:complications; D006801:Humans; D008875:Middle Aged; D012044:Regression Analysis; D015203:Reproducibility of Results; D012307:Risk Factors