Framework for an Interactive Assistance in Diagnostic Processes Based on Probabilistic Modeling of Clinical Practice Guidelines☆

Philipp, Patrick; Fischer, Yvonne; Hempel, Dirk; Beyerer, Jürgen

doi:10.1016/b978-0-12-804203-8.00026-2

Cited by 7 publications

(13 citation statements)

References 30 publications

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“…A CPG can be transformed into a UML activity by an expert's dialog or by the medical expert himself. An activity serves as an interface to the models used for providing the actual assistance functions [2], [5].…”

Section: Semi-automatic Translationmentioning

confidence: 99%

“…These models can be (semi-) automatically generated by only one given activity. In [2], [5] we introduced the translation from UML activities into Bayesian nets (see Figure 1). In this paper we focus on the translation of UML activities into Petri nets.…”

Section: Modeling Approachmentioning

confidence: 99%

“…In (5) all actions and concurrency nodes of the UML activity are transformed into transitions of the Petri net. Additionally, in (6) transitions are added for activity edges between branch nodes, initial node and end nodes.…”

Section: B Translation From Uml Activity To Petri Netmentioning

confidence: 99%

“…patient's wishes, medical equipment) [3], [4]. Consequently, there is a gap between theoretical knowledge on the one side and practical solutions on the other side [5]. In addition, barriers can arise if a guideline is not fully accepted by the expert.…”

Section: Introductionmentioning

confidence: 99%

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Framework for an Interactive Assistance in Diagnostic Processes Based on the Translation of UML Activities into Petri Nets

Philipp

Fischer

Hempel

et al. 2015

2015 International Conference on Computational Science and Computational Intelligence (CSCI)

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In contemporary medicine, diagnostic processes provided by Clinical Practice Guidelines (CPGs) play a key role. A CPG provides recommendations that open up a scope of actions for the medical practitioner. But there is a gap between theoretical knowledge and practical solutions. Furthermore, barriers of implementation can arise. Taking these challenges into account, we propose a framework for facilitating the implementation of diagnostic processes. For this reason, the CPGs of Chronic Myeloid Leukemia (CML) and Myelodysplastic Syndromes (MDS) are modeled using Unified Modeling Language (UML). A UML activity serves as a basis for more complex models that are used to provide the actual assistance functions. This paper focuses on the automatic translation of UML activities into Petri nets.

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Section: Semi-automatic Translationmentioning

confidence: 99%

Section: Modeling Approachmentioning

confidence: 99%

Section: B Translation From Uml Activity To Petri Netmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Framework for an Interactive Assistance in Diagnostic Processes Based on the Translation of UML Activities into Petri Nets

Philipp

Fischer

Hempel

et al. 2015

2015 International Conference on Computational Science and Computational Intelligence (CSCI)

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“…The use of assistance functions for diagnosis and surgical interventions has become an evolving area for mastering challenges of contemporary medicine. Inter alia, these assistance functions can help to prevent malpractices, optimize treatment and preserve a high level of satisfaction for patients as well as employees (Philipp, Fischer, Hempel, & Beyerer, 2016), (Lalys & Jannin, 2014).…”

Section: Introductionmentioning

confidence: 99%

Towards a Surgical Phase Detection Using Markov Logic Networks

Philipp¹,

Bleier²,

Fischer³

et al.

EPiC Series in Health Sciences

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The use of assistance functions for diagnosis and surgical interventions has become an evolving area for mastering challenges of contemporary medicine. Inter alia, these assistance functions can help to prevent malpractices and preserve a high level of satisfaction for patients as well as employees.To enable such functions in context of a computer-assisted orthopaedic surgery (CAOS), we elaborate the use of Markov Logic Networks (MLNs) for modelling surgical phases. In contrast to commonly researched systems for surgical process modelling, MLNs combine rule-based as well as probabilistic approaches. This allows us to integrate soft and hard constraints into our network – which greatly expands the scenery of currently researched models for phase detection in surgical interventions.In our contribution, we present the necessary fundamentals of MLNs and show the application to a comprehensible test case. The results are promising concerning the use of MLNs for surgical phase detection. In particular, MLNs have shown two advantages: Firstly, due to their template characteristics, few logic rules allow to model numerous interdependencies between the different surgical phases. Secondly, the combination of probabilistic and logic approaches allows to handle sensor inaccuracies and misclassifications of features directly. E.g., the inaccuracy of a sensor can be expressed by reducing the weight of corresponding formulas, allowing for a softening of constraints.

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Expert-based probabilistic modeling of workflows in context of surgical interventions

Philipp

Beyerer

Fischer

2017

2017 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA)

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To provide assistance functions in context of surgical interventions, the use of medical workflows plays an important role. Workflow models can be used to assess the progress of an on-going surgery, enabling tailored (i.e., context sensitive) support for the medical practitioner. Subsequently, this provides opportunities to prevent malpractices, to enhance the patient's outcome and to preserve a high level of satisfaction. In this work, we propose a framework which enables a formalization of medical workflows. It is driven by a dialog of medical as well as technical experts and is based on the Unified Modeling Language (UML). An easy comprehensible UML activity serves as a starting point for the automatic generation of more complex models that can be used for the actual estimation of the progress of a surgical intervention. In this work, we present translation rules, which allow to transfer a given UML activity into a Dynamic Bayesian Network (DBN). The methods are presented for the application example of a cholecystectomy (surgical removal of the gallbladder)

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Framework for an Interactive Assistance in Diagnostic Processes Based on Probabilistic Modeling of Clinical Practice Guidelines☆

Cited by 7 publications

References 30 publications

Framework for an Interactive Assistance in Diagnostic Processes Based on the Translation of UML Activities into Petri Nets

Framework for an Interactive Assistance in Diagnostic Processes Based on the Translation of UML Activities into Petri Nets

Towards a Surgical Phase Detection Using Markov Logic Networks

Expert-based probabilistic modeling of workflows in context of surgical interventions

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