Multisolutional clustering and quantization algorithm (MCQ)

I. Dvorchik, W. Marsh, V. Gurari, M. Subotin, H. R. Doyle

Research output: Contribution to journalArticlepeer-review


We have developed a novel clustering and quantization algorithm that allows the user to create multiple one-to-one correspondences between the actual data and its transformed (clustered and quantized) values, based on the user's hypothesis regarding the nature of the classification task. The types of problems for which the algorithm can be beneficial are discussed. We report experiments employing simulated and real data that suggest the proposed algorithm may be useful in neural network analysis of various phenomena in medicine and biology.

Original languageEnglish (US)
Pages (from-to)439-450
Number of pages12
JournalComputers in Biology and Medicine
Issue number5
StatePublished - Sep 1996
Externally publishedYes


  • Algorithms
  • Atrioventricular node
  • Cluster analysis
  • Computer
  • Models
  • Neural networks
  • Theoretical
  • Vector quantization

ASJC Scopus subject areas

  • Computer Science Applications
  • Health Informatics


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