PMID: 9638379Jun 25, 1998Paper

Evaluation of a statistically derived decision tree for the cytodiagnosis of fine needle aspirates of the breast (FNAB)

Cytopathology : Official Journal of the British Society for Clinical Cytology
S S CrossZ Ma

Abstract

A decision tree for the diagnosis of FNAB was derived from defined human observations using a rule induction method, C4.5 (a derivative of the ID3 algorithm). This algorithm is an implementation of the top-down induction method where the tree is determined iteratively by adding those nodes and branches which maximize the information gain at each step. The tree was derived from a training set of 200 FNAB with known outcome using 10 defined features (from one observer) and patient age. The tree contained a total of seven nodes (six observable features and patient age) with eight endpoints (four benign, four malignant). The tree was applied to a test set of 400 further FNAB with observations from the training observer and produced a sensitivity of 95%, specificity of 93% and a positive predictive value (PPV) of a malignant result of 89%. Four trainee pathologists were given a training session on the observable features and then used the tree to determine outcome in a further 50 FNAB. The observers were blind to clinical details apart from age and the endpoints were coded with letters and not labelled benign or malignant. The results from these observers produced ranges of sensitivity 80-96%, specificity 64-92%, PPV 73-92% and kapp...Continue Reading

Citations

Apr 17, 2007·Computers in Biology and Medicine·Nicandro Cruz-RamírezRocío Erandi Barrientos-Martínez
Jun 14, 2013·Computational and Mathematical Methods in Medicine·Cruz-Ramírez NicandroBarrientos-Martínez Rocío Erandi
Feb 26, 2015·Cadernos de saúde pública·Priscyla Waleska SimõesMaria Inês Rosa

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