selected clinical applications i or · selected clinical applications i or the way from a bayesian...
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Mario A. Cypko
eHealth Summit Austria 2016
Selected clinical applications I
or
the way from a Bayesian Network
to a Clinical Decision Support System
for Tumor Boards
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Head&Neck-Tumorboard at the University Hospital Leipzig, Germany
Complexity of tumor board decisions
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Probabilistic Modelling example of laryngeal cancer
Bayes’sches Netzwerk (J.Pearl)
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3 years of devlopment 1 Physican & 1 Computer Scientist 1. year, daily
2. year, twice a week 3. year, once a week
Aim: To model a tumor board decision for laryngeal cancer.
An example of the MEBN therapy decision of laryngeal cancer, >1100 IEs and >1500 dependencies
CDSS using BN – Treatment Decision of Laryngeal Cancer
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Cypko MA, Stöhr M, Denecke K, Dietz A, Lemke H U. “User interaction with MEBNs for large patient specific
treatment decision models with an example for laryngeal cancer” Int J CARS, 9 (Suppl 1), 2014.
Concept for a CDSS using BN
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BN limitation of :
Fuzzy values to decreas data validity over time
Repositories, engines and transmission
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Limits in BN modelling
- Information about time is needed. - Recalculating fuzzy values based on past time of examinations
Gaebel J, Stoehr M, Cypko MA. “Integrating Intelligent Agents in form of Arden Syntax for Computing Instance Based Fuzziness into Patient-Specific Bayesian Networks” Int J CARS, 11 (1), 2016.
e.g., Arden Syntax Additional Tools
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Cypko MA, Stöhr M, Denecke K, Dietz A, Lemke H U. “User interaction with MEBNs for large patient specific
treatment decision models with an example for laryngeal cancer” Int J CARS, 9 (Suppl 1), 2014.
Concept for a CDSS using BN
![Page 15: Selected clinical applications I or · Selected clinical applications I or the way from a Bayesian Network to a Clinical Decision Support System ... Concept for a CDSS using BN](https://reader034.vdocuments.us/reader034/viewer/2022042118/5e96f39ddc43df3f614c7691/html5/thumbnails/15.jpg)
Expert-Based Probabilistic Modelling
L.C. van der Gaag et. al. 2005
BMT 2015 –Lübeck [email protected]
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Cypko MA, Stöhr M, Denecke K, Dietz A, Lemke H U. “User interaction with MEBNs for large patient specific
treatment decision models with an example for laryngeal cancer” Int J CARS, 9 (Suppl 1), 2014.
Concept for a CDSS using BN
Users UID Viewpoints
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GUI - Examples
Therapy decision model with an example of Larnygeal cancer
Lemke HU, Cypko MA, Warner D, Berliner L..3D++ Visualisation of MEBN Graphs and Screen Representations of Patient Models (PIXIE II). Stud Health Technol Inform. 2014;196:248-51.
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Questions? Thank you!
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Meet our digital OR!
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Pre-analysis Treatment decision
Repositories, engines and transmission
• Decision making: Multi-Entity Bayesian Networks • Scoring Systems: Arden Syntax
Example of Mitral insufficiency
Aggre-gation of patient
data
X X
Risk Determination
(Scores)
Selection of
implant
Typ- & degree of severity
Feasibility analysis
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Established medical knowledge e.g.,
e.g., Arden Syntax Additional Tools
Repositories, engines and transmission
Established data storage and transmission
Cypko MA, Lemke HU. “Concepts for IHE integration profiles for communication with probabilistic graphical models.” Int J CARS, 11 (1), 2016.