Deep models and their relation to diagnosis Academic Article uri icon

abstract

  • In this paper we distinguish between deep models in the sense of scientific first principles and deep cognitive models where the problem solver has a qualitative symbolic representation of the system or device that accounts for how the system 'works'. We analyze diagnostic reasoning as an information processing task, identifying the generic types of knowledge (and reasoning) needed for the task to be performed adequately. If these are available, an integrated collection of generic problem solvers can produce a diagnostic conclusion. The need for deep or causal models arises when some or all of these types of knowledge are missing in the problem solver. We provide a typology of different knowledge structures and reasoning processes that play a role in qualitative or functional reasoning and elaborate on functional representations as deep cognitive models for some aspects of causal reasoning in medicine. 1989.

published proceedings

  • Artificial Intelligence in Medicine

author list (cited authors)

  • Chandrasekaran, B., Smith, J. W., & Sticklen, J.

citation count

  • 40

complete list of authors

  • Chandrasekaran, B||Smith, JW||Sticklen, Jon

publication date

  • January 1989