Evaluating a neural network decision-support tool for the diagnosis of breast cancer

  • Joseph Downs
  • Robert F Harrison
  • Simon S Cross
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 934)


This paper describes the evaluation of an application of the ARTMAP neural network model to the diagnosis of cancer from fine-needle aspirates of the breast. The network has previously demonstrated very high performance when used with high-quality data provided by an expert pathologist. New performance results are provided for its use with “noisy” data provided by an inexperienced pathologist. Additionally, ARTMAP supports the extraction of symbolic rules from a trained network and the validity of these autonomously-acquired rules is discussed. It is concluded that the symbolic rules provide an appropriate mapping of input features to category classes in the domain. However, the network in its present form is only suitable for use as a decision-support tool by a senior pathologist, since its performance deteriorated greatly with poor-quality data provided by a junior pathologist. The implications of the findings are discussed.


Radial Basis Function Network Vote Strategy Rule Extraction Category Cluster Fine Needle Aspirate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    G.A. Carpenter and S. Grossberg (1987) A Massively Parallel Architecture for a Self-Organizing Neural Pattern Recognition Machine, Computer Vision, Graphics and Image Processing, 37, 54–115.Google Scholar
  2. [2]
    G.A. Carpenter, S. Grossberg, N. Markuzon, J.H. Reynolds and D.B. Rosen (1992) Fuzzy ARTMAP: A Neural Network Architecture for Incremental Supervised Learning of Analog Multidimensional Maps, IEEE Transactions on Neural Networks, 3(5), 698–712.CrossRefGoogle Scholar
  3. [3]
    G.A. Carpenter, S. Grossberg and J.H. Reynolds (1991) ARTMAP: Supervised Real-Time Learning and Classification of Nonstationary Data by a Self-Organizing Neural Network, Neural Networks, 4(5), 565–588.CrossRefGoogle Scholar
  4. [4]
    G.A. Carpenter and A.H. Tan (1993) Rule Extraction, Fuzzy ARTMAP, and Medical Databases, Proceedings of the World Congress on Neural Networks, Volume I, 501–506.Google Scholar
  5. [5]
    S.S. Cross, T.J. Stephenson, Y. Diez, R.F. Harrison, J.C.E. Underwood and J. Downs (In Press) Diagnosis of Breast Fine Needle Aspirates Using Human Observations and a Multi-Layer Perceptron Neural Network, to appear in J. Pathol..Google Scholar
  6. [6]
    G. Cybenko (1989) Approximations by Superpositions of a Sigmoidal Function, Mathematics of Control, Signals and Systems, 2, 303–314.Google Scholar
  7. [7]
    J. Downs, R.F. Harrison and S.S. Cross (In Press) A Neural Network Decision Support Tool for the Diagnosis of Breast Cancer, to appear in Proceedings of the 10th Conference of the Society for the Study of Artificial Intelligence and Simulation of Behaviour (AISB-95). Amsterdam: IOS Press.Google Scholar
  8. [8]
    J. Downs, R.F. Harrison and R.L. Kennedy (1995) A Prototype Neural Network Decision Support Tool for the Diagnosis of Acute Myocardial Infarction, this volume.Google Scholar
  9. [9]
    S.A.C. Dundas, P.R. Sanderson, H. Matta and A.J. Shorthouse (1988) Fine Needle Aspiration of Palpable Breast Lesions: Results Obtained with Cytocentrifuge Preparation of Aspirates, Acta Cytologica, 32, 202–206.PubMedGoogle Scholar
  10. [10]
    C.W. Elston and I.O. Ellis (1990) Pathology and Breast Screening, Histopathology, 16, 109–118.PubMedGoogle Scholar
  11. [11]
    P.W. Hamilton, N. Anderson, P.H. Bartels and D. Thompson (1994) Expert System Support Using Bayesian Belief Networks in the Diagnosis of Fine Needle Aspiration Biopsy Specimens of the Breast, J. Clin. Pathol., 47, 329–336.PubMedGoogle Scholar
  12. [12]
    R.F. Harrison, C.P. Lim and R.L. Kennedy (1994) Autonomously Learning Neural Networks for Clinical Decision Support. In: E.C. Ifeachor and K.G. Rosen, (Eds.) Proceedings of the International Conference on Neural Networks and Expert Systems in Medicine and Healthcare (NNESMED-94), Plymouth, UK, 15–22.Google Scholar
  13. [13]
    F. Hayes-Roth, D.A. Waterman and D.B. Lenat (1983) Building Expert Systems. London: Addison-Wesley.Google Scholar
  14. [14]
    H.A. Heathfield, N. Kirkham, I.O. Ellis and G. Winstanley (1990) Computer Assisted Diagnosis of Fine Needle Aspirates of the Breast, J. Clin. Pathol., 43, 168–170.PubMedGoogle Scholar
  15. [15]
    C.P. Lim and R.F. Harrison (In Press) Modified Fuzzy ARTMAP Approaches Bayes Optimal Classification Rates: An Empirical Demonstration, to appear in Neural Networks.Google Scholar
  16. [16]
    J. Moody and C. Darken (1989) Fast Learning in Networks of Locally-Tuned Processing Units, Neural Computation, 1, 281–294.Google Scholar
  17. [17]
    J. Park and I. Sandberg (1991) Universal Approximation Using Radial Basis Function Networks, Neural Computation, 3, 246–257.Google Scholar
  18. [18]
    J.R. Quinlan (1986) Induction of Decision Trees, Machine Learning, 1, 81–106.Google Scholar
  19. [19]
    D. Rumelhart, G. Hinton and R. Williams (1986) Learning Representations by Back-Propagating Errors, Nature, 323, 533–536.Google Scholar
  20. [20]
    P.B. Silcocks (1983) Measuring Repeatability and Validity of Histological Diagnosis-A Brief Review with Some Practical Examples, J. Clin. Pathol., 36, 1269–1275.PubMedGoogle Scholar
  21. [21]
    R.D. Start, P.B. Silcocks, S.S. Cross and J.H.F. Smith (1992) Problems with Audit of a New Fine-Needle Aspiration Service in a District General Hospital, J. Pathol., 167, 141A.Google Scholar
  22. [22]
    G.Towell and J.W. Shavlik (1993) Extracting Refined Rules from Knowledge-Based Neural Networks, Machine Learning, 13(1), 71–101.Google Scholar
  23. [23]
    J.C.E. Underwood (1992) Tumours: Benign and Malignant. In: J.C.E. Underwood, (Ed.) General and Systematic Pathology, 223–246. Edinburgh: Churchill Livingstone.Google Scholar
  24. [24]
    CA.Wells, I.O. Ellis, H.D. Zakhour and A.R. Wilson (1994) Guidelines for Cytology Procedures and Reporting on Fine Needle Aspirates of the Breast, Cytopathology, 5, 316–334.PubMedGoogle Scholar
  25. [25]
    W.H. Wolberg and O.L. Mangasarian (1993) Computer-Designed Expert Systems for Breast Cytology Diagnosis, Anal. Quant. Cytol. Histol., 15, 67–74.PubMedGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • Joseph Downs
    • 1
  • Robert F Harrison
    • 1
  • Simon S Cross
    • 2
  1. 1.Dept. of Automatic Control and Systems EngineeringUniversity of SheffieldSheffieldUK
  2. 2.Dept. of PathologyUniversity of Sheffield Medical SchoolSheffieldUK

Personalised recommendations