A new strategy for clinical decision making: Censors and neuroendocrinological diseases

Hormoz Mansour*, Mark E Molitch

*Corresponding author for this work

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

A patient rarely has a single, isolated disease. The situation is usually much more complex since the different parts of the human organism and its metabolism interact with each other on multiple levels and follow several feedback patterns. These interactions and feedback patterns become even more complex when the effects of the external environment are considered. When several diseases are present, the first steps in medical diagnosis are to determine whether one of the diseases interacts with ("Censors") or changes the significant symptoms, signs, or results of the laboratory tests of the other diseases. We will try, within this paper, to go beyond the scope of the first generation of Artificial Intelligence systems in medicine to determine the effects of two diseases on each other. One important part of the effect of two diseases on each other is the effect of Censors. In addition, causal reasoning, reasoning by analogy, and learning from precedents are important and necessary for a human-like expert in medicine. Their application to thyroid diseases, with an implemented system, are considered in this paper.

Original languageEnglish (US)
Pages (from-to)215-221
Number of pages7
JournalComputers in Biology and Medicine
Volume16
Issue number3
DOIs
StatePublished - Jan 1 1986

Keywords

  • Analogy
  • Censor
  • Clinical decision making
  • Learning
  • Nonmonotonic reasoning
  • Thyroid

ASJC Scopus subject areas

  • Computer Science Applications
  • Health Informatics

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