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Journal ArticleDOI

An integrated two-level hierarchical system for decision making in radiation therapy based on fuzzy cognitive maps

TLDR
A novel approach introduces fuzzy cognitive maps (FCMs) as the computational modeling method, which tackles the complexity and allows the analysis and simulation of the clinical radiation procedure.
Abstract
Radiation therapy decision-making is a complex process that has to take into consideration a variety of interrelated functions. Many fuzzy factors that must be considered in the calculation of the appropriate dose increase the complexity of the decision-making problem. A novel approach introduces fuzzy cognitive maps (FCMs) as the computational modeling method, which tackles the complexity and allows the analysis and simulation of the clinical radiation procedure. Specifically this approach is used to determine the success of radiation therapy process estimating the final dose delivered to the target volume, based on the soft computing technique of FCMs. Furthermore a two-level integrated hierarchical structure is proposed to supervise and evaluate the radiotherapy process prior to treatment execution. The supervisor determines the treatment variables of cancer therapy and the acceptance level of final radiation dose to the target volume. Two clinical case studies are used to test the proposed methodology and evaluate the simulation results. The usefulness of this two-level hierarchical structure discussed and future research directions are suggested for the clinical use of this methodology.

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Citations
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Journal ArticleDOI

Active Hebbian learning algorithm to train fuzzy cognitive maps

TL;DR: This proposed learning procedure is a promising approach for exploiting experts' involvement with their subjective reasoning and at the same time improving the effectiveness of the FCM operation mode and thus it broadens the applicability of FCMs modeling for complex systems.
Journal ArticleDOI

Learning Algorithms for Fuzzy Cognitive Maps—A Review Study

TL;DR: A survey on recent advances on learning methodologies and algorithms for FCMs that present their dynamic capabilities and application characteristics in diverse scientific fields is established.
Book ChapterDOI

Fuzzy Cognitive Map Learning Based on Nonlinear Hebbian Rule

TL;DR: This research work proposes the utilization of the unsupervised Hebbian algorithm to nonlinear units for training FCMs and proposes the proposed learning procedure, which modifies its fuzzy causal web as causal patterns change and as experts update their causal knowledge.
Journal ArticleDOI

A new methodology for Decisions in Medical Informatics using fuzzy cognitive maps based on fuzzy rule-extraction techniques

TL;DR: A new methodology through a framework for decision making tasks using the soft computing technique of FCMs based on knowledge extraction methods is presented, presented to illustrate the application of the proposed framework and its functioning.
Journal ArticleDOI

Fuzzy cognitive map architectures for medical decision support systems

TL;DR: Fuzzy cognitive maps are suitable for medical decision support systems and appropriate FCM architectures are proposed and developed as well as the corresponding examples from two medical disciplines, i.e. speech and language pathology and obstetrics, are described.
References
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Journal ArticleDOI

Fuzzy cognitive maps

TL;DR: A fuzzy causal algebra for governing causal propagation on FCMs is developed and it allows knowledge bases to be grown by connecting different FCMs.
Book

Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems

TL;DR: Neural Fuzzy Systems provides a comprehensive, up-to-date introduction to the basic theories of fuzzy systems and neural networks, as well as an exploration of how these two fields can be integrated to create Neural-Fuzzy systems.
Journal ArticleDOI

Calculation of complication probability factors for non-uniform normal tissue irradiation: the effective volume method.

TL;DR: A method has been developed to calculate complication probability factors for non-uniformly irradiated normal organs using dose volume histograms and complication probabilities for uniform partial organ irradiation, and the method is shown to obey various boundary conditions.