---
res:
  bibo_abstract:
  - This paper presents preliminary work on the formalization of three prominent cognitive
    biases in the diagnostic reasoning process over epileptic seizures, psychogenic
    seizures and syncopes. Diagnostic reasoning is understood as iterative exploration
    of medical evidence. This exploration is represented as a partially observable
    Markov decision process where the state (i.e., the correct diagnosis) is uncertain.
    Observation likelihoods and belief updates are computed using a Bayesian network
    which defines the interrelation between medical risk factors, diagnoses and potential
    findings. The decision problem is solved via partially observable upper confidence
    bounds for trees in Monte-Carlo planning. We compute a biased diagnostic exploration
    policy by altering the generated state transition, observation and reward during
    look ahead simulations. The resulting diagnostic policies reproduce reasoning
    errors which have only been described informally in the medical literature. We
    plan to use this formal representation in the future to inversely detect and classify
    biased reasoning in actual diagnostic trajectories obtained from physicians.@eng
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Dominik
      foaf_name: Battefeld, Dominik
      foaf_surname: Battefeld
      foaf_workInfoHomepage: http://www.librecat.org/personId=91864
    orcid: 0000-0002-5480-0594
  - foaf_Person:
      foaf_givenName: Stefan
      foaf_name: Kopp, Stefan
      foaf_surname: Kopp
  dct_date: 2022^xs_gYear
  dct_language: eng
  dct_subject:
  - Diagnostic reasoning
  - Cognitive bias
  - Cognitive model
  - POMDP
  - Bayesian network
  - Epilepsy
  - CDSS
  dct_title: Formalizing cognitive biases in medical diagnostic reasoning@
...