---
_id: '56477'
abstract:
- lang: eng
  text: We describe a prototype of a Clinical Decision Support System (CDSS) that
    provides (counterfactual) explanations to support accurate medical diagnosis.
    The prototype is based on an inherently interpretable Bayesian network (BN). Our
    research aims to investigate which explanations are most useful for medical experts
    and whether co-constructing explanations can foster trust and acceptance of CDSS.
author:
- first_name: Felix
  full_name: Liedeker, Felix
  id: '93275'
  last_name: Liedeker
- first_name: Philipp
  full_name: Cimiano, Philipp
  last_name: Cimiano
citation:
  ama: 'Liedeker F, Cimiano P. A Prototype of an Interactive Clinical Decision Support
    System with Counterfactual Explanations. In: ; 2023.'
  apa: Liedeker, F., &#38; Cimiano, P. (2023). <i>A Prototype of an Interactive Clinical
    Decision Support System with Counterfactual Explanations</i>. xAI-2023 Late-breaking
    Work, Demos and Doctoral Consortium co-located with the 1st World Conference on
    eXplainable Artificial Intelligence (xAI-2023), Lissabon.
  bibtex: '@inproceedings{Liedeker_Cimiano_2023, title={A Prototype of an Interactive
    Clinical Decision Support System with Counterfactual Explanations}, author={Liedeker,
    Felix and Cimiano, Philipp}, year={2023} }'
  chicago: Liedeker, Felix, and Philipp Cimiano. “A Prototype of an Interactive Clinical
    Decision Support System with Counterfactual Explanations,” 2023.
  ieee: F. Liedeker and P. Cimiano, “A Prototype of an Interactive Clinical Decision
    Support System with Counterfactual Explanations,” presented at the xAI-2023 Late-breaking
    Work, Demos and Doctoral Consortium co-located with the 1st World Conference on
    eXplainable Artificial Intelligence (xAI-2023), Lissabon, 2023.
  mla: Liedeker, Felix, and Philipp Cimiano. <i>A Prototype of an Interactive Clinical
    Decision Support System with Counterfactual Explanations</i>. 2023.
  short: 'F. Liedeker, P. Cimiano, in: 2023.'
conference:
  end_date: 2023-07-28
  location: Lissabon
  name: xAI-2023 Late-breaking Work, Demos and Doctoral Consortium co-located with
    the 1st World Conference on eXplainable Artificial Intelligence (xAI-2023)
  start_date: 2023-07-26
date_created: 2024-10-09T14:50:09Z
date_updated: 2024-10-09T15:04:53Z
department:
- _id: '660'
keyword:
- Explainable AI
- Clinical decision support
- Bayesian network
- Counterfactual explanations
language:
- iso: eng
project:
- _id: '128'
  name: 'TRR 318 - C5: TRR 318 - Subproject C5'
status: public
title: A Prototype of an Interactive Clinical Decision Support System with Counterfactual
  Explanations
type: conference
user_id: '93275'
year: '2023'
...
---
_id: '51343'
abstract:
- lang: eng
  text: 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.
author:
- first_name: Dominik
  full_name: Battefeld, Dominik
  id: '91864'
  last_name: Battefeld
  orcid: 0000-0002-5480-0594
- first_name: Stefan
  full_name: Kopp, Stefan
  last_name: Kopp
citation:
  ama: 'Battefeld D, Kopp S. Formalizing cognitive biases in medical diagnostic reasoning.
    In: <i>Proceedings of the 8th Workshop on Formal and Cognitive Reasoning</i>.
    ; 2022.'
  apa: Battefeld, D., &#38; Kopp, S. (2022). Formalizing cognitive biases in medical
    diagnostic reasoning. <i>Proceedings of the 8th Workshop on Formal and Cognitive
    Reasoning</i>. 8th Workshop on Formal and Cognitive Reasoning (FCR), Trier.
  bibtex: '@inproceedings{Battefeld_Kopp_2022, title={Formalizing cognitive biases
    in medical diagnostic reasoning}, booktitle={Proceedings of the 8th Workshop on
    Formal and Cognitive Reasoning}, author={Battefeld, Dominik and Kopp, Stefan},
    year={2022} }'
  chicago: Battefeld, Dominik, and Stefan Kopp. “Formalizing Cognitive Biases in Medical
    Diagnostic Reasoning.” In <i>Proceedings of the 8th Workshop on Formal and Cognitive
    Reasoning</i>, 2022.
  ieee: D. Battefeld and S. Kopp, “Formalizing cognitive biases in medical diagnostic
    reasoning,” presented at the 8th Workshop on Formal and Cognitive Reasoning (FCR),
    Trier, 2022.
  mla: Battefeld, Dominik, and Stefan Kopp. “Formalizing Cognitive Biases in Medical
    Diagnostic Reasoning.” <i>Proceedings of the 8th Workshop on Formal and Cognitive
    Reasoning</i>, 2022.
  short: 'D. Battefeld, S. Kopp, in: Proceedings of the 8th Workshop on Formal and
    Cognitive Reasoning, 2022.'
conference:
  end_date: 2022-09-23
  location: Trier
  name: 8th Workshop on Formal and Cognitive Reasoning (FCR)
  start_date: '2022-09-19 '
date_created: 2024-02-14T09:06:04Z
date_updated: 2024-10-31T10:00:01Z
ddc:
- '000'
department:
- _id: '660'
file:
- access_level: closed
  content_type: application/pdf
  creator: doba2
  date_created: 2024-10-31T09:59:46Z
  date_updated: 2024-10-31T09:59:46Z
  file_id: '56846'
  file_name: paper8.pdf
  file_size: 261528
  relation: main_file
  success: 1
file_date_updated: 2024-10-31T09:59:46Z
has_accepted_license: '1'
keyword:
- Diagnostic reasoning
- Cognitive bias
- Cognitive model
- POMDP
- Bayesian network
- Epilepsy
- CDSS
language:
- iso: eng
project:
- _id: '128'
  name: 'TRR 318 - C5: TRR 318 - Subproject C5'
publication: Proceedings of the 8th Workshop on Formal and Cognitive Reasoning
quality_controlled: '1'
status: public
title: Formalizing cognitive biases in medical diagnostic reasoning
type: conference
user_id: '91864'
year: '2022'
...
---
_id: '9976'
abstract:
- lang: eng
  text: State-of-the-art mechatronic systems offer inherent intelligence that enables
    them to autonomously adapt their behavior to current environmental conditions
    and to their own system state. This autonomous behavior adaptation is made possible
    by software in combination with complex sensor and actuator systems and by sophisticated
    information processing, all of which make these systems increasingly complex.
    This increasing complexity makes the design process a challenging task and brings
    new complex possibilities for operation and maintenance. However, with the risk
    of increased system complexity also comes the chance to adapt system behavior
    based on current reliability, which in turn increases reliability. The development
    of such an adaption strategy requires appropriate methods to evaluate reliability
    based on currently selected system behavior. A common approach to implement such
    adaptivity is to base system behavior on different working points that are obtained
    using multiobjective optimization. During operation, selection among these allows
    a changed operating strategy. To allow for multiobjective optimization, an accurate
    system model including system reliability is required. This model is repeatedly
    evaluated by the optimization algorithm. At present, modeling of system reliability
    and synchronization of the models of behavior and reliability is a laborious manual
    task and thus very error-prone. Since system behavior is crucial for system reliability,
    an integrated model is introduced that integrates system behavior and system reliability.
    The proposed approach is used to formulate reliability-related objective functions
    for a clutch test rig that are used to compute feasible working points using multiobjective
    optimization.
author:
- first_name: Thorben
  full_name: Kaul, Thorben
  id: '14802'
  last_name: Kaul
- first_name: Tobias
  full_name: Meyer, Tobias
  last_name: Meyer
- first_name: Walter
  full_name: Sextro, Walter
  id: '21220'
  last_name: Sextro
citation:
  ama: Kaul T, Meyer T, Sextro W. Formulation of reliability-related objective functions
    for design of intelligent mechatronic systems. <i>SAGE Journals</i>. 2017;Vol.
    231(4):390-399. doi:<a href="https://doi.org/10.1177/1748006X17709376">10.1177/1748006X17709376</a>
  apa: Kaul, T., Meyer, T., &#38; Sextro, W. (2017). Formulation of reliability-related
    objective functions for design of intelligent mechatronic systems. <i>SAGE Journals</i>,
    <i>Vol. 231(4)</i>, 390–399. <a href="https://doi.org/10.1177/1748006X17709376">https://doi.org/10.1177/1748006X17709376</a>
  bibtex: '@article{Kaul_Meyer_Sextro_2017, title={Formulation of reliability-related
    objective functions for design of intelligent mechatronic systems}, volume={Vol.
    231(4)}, DOI={<a href="https://doi.org/10.1177/1748006X17709376">10.1177/1748006X17709376</a>},
    journal={SAGE Journals}, author={Kaul, Thorben and Meyer, Tobias and Sextro, Walter},
    year={2017}, pages={390–399} }'
  chicago: 'Kaul, Thorben, Tobias Meyer, and Walter Sextro. “Formulation of Reliability-Related
    Objective Functions for Design of Intelligent Mechatronic Systems.” <i>SAGE Journals</i>
    Vol. 231(4) (2017): 390–99. <a href="https://doi.org/10.1177/1748006X17709376">https://doi.org/10.1177/1748006X17709376</a>.'
  ieee: T. Kaul, T. Meyer, and W. Sextro, “Formulation of reliability-related objective
    functions for design of intelligent mechatronic systems,” <i>SAGE Journals</i>,
    vol. Vol. 231(4), pp. 390–399, 2017.
  mla: Kaul, Thorben, et al. “Formulation of Reliability-Related Objective Functions
    for Design of Intelligent Mechatronic Systems.” <i>SAGE Journals</i>, vol. Vol.
    231(4), 2017, pp. 390–99, doi:<a href="https://doi.org/10.1177/1748006X17709376">10.1177/1748006X17709376</a>.
  short: T. Kaul, T. Meyer, W. Sextro, SAGE Journals Vol. 231(4) (2017) 390–399.
date_created: 2019-05-27T09:37:46Z
date_updated: 2019-09-16T10:20:49Z
department:
- _id: '151'
doi: 10.1177/1748006X17709376
keyword:
- Integrated model
- reliability
- system behavior
- Bayesian network
- multiobjective optimization
language:
- iso: eng
page: 390 - 399
publication: SAGE Journals
quality_controlled: '1'
status: public
title: Formulation of reliability-related objective functions for design of intelligent
  mechatronic systems
type: journal_article
user_id: '55222'
volume: Vol. 231(4)
year: '2017'
...