Statistical approach to fine needle aspiration diagnosis of breast masses

W. H. Wolberg, M. A. Tanner, W. Y. Loh, N. Vanichsetakul

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)737-741
Number of pages5
JournalActa Cytologica
Volume31
Issue number6
StatePublished - 1987

ASJC Scopus subject areas

  • Pathology and Forensic Medicine
  • Histology

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