Statistical approach to fine needle aspiration diagnosis of breast masses
Wolberg, W.H.; Tanner, M.A.; Loh, W.Y.; Vanichsetakul, N.
Acta Cytologica 31(6): 737-741
1987
ISSN/ISBN: 0001-5547 PMID: 3425134 Document Number: 295932
A statistical algorithm was used for recursively partitioning a consecutive series of 37 benign and 69 malignant fine needle aspirates to produce a decision tree for diagnosing breast masses. Optimal separation between benign and malignant cytology was accomplished by evaluating clump characteristics when clumps were present and evaluating cell integrity when clumps were absent. The 1.5% false-negative and 9.7% false-positive rates obtained through this scheme are better than those reported for most series.