Possibility-probability relation in medical models

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Medical models based on possibility theory are usually much simpler than those based on probability theory, but they lack foundations. The most foundational question is: How to obtain a possibility distribution for a modeling process? As one of the solutions, a simple framework is proposed built on the conjecture that a probability distribution for an uncertain process can be predicted by the process's possibility distribution. The case of the perfect prediction and the case of possibility and probability distributions related less than perfect (modeling "ideal body weight") are considered in this paper.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsPetra Perner, Rudiger Brause, Hermann-Georg Holzhutter
PublisherSpringer Verlag
Pages1-8
Number of pages8
ISBN (Print)354020282X, 9783540202820
DOIs
StatePublished - 1 Jan 2003

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2868
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Keywords

  • Possibilistic modeling in medicine and biology
  • Possibility distribution function
  • Possibility theory
  • Probability
  • Probability density function

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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