The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
An integrated two-level hierarchical system for decision making in radiation therapy based on fuzzy cognitive maps
Abstract
The 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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Kosko, B. (1986) · International Journal of Man-Machine Studies · doi:10.1016/s0020-7373(86)80040-2 · Cited by 3,576
Cited by
Fuzzy logic in medicine and bioinformatics
Torres, A., & Nieto, J. J. (2006) · BioMed Research International · doi:10.1155/jbb/2006/91908 · Cited by 207
Papageorgiou, E. I., Markinos, A. T., & Gemtos, T. A. (2011) · Applied Soft Computing · doi:10.1016/j.asoc.2011.01.036 · Cited by 157
Self-citation
Metadata
- Authors
- Papageorgiou, E. I., Stylios, C. D., & Groumpos, P. P.
- Venue
- IEEE Transactions on Biomedical Engineering
- Published
- 2003-12
- Volume
- 50
- Issue
- 12
- Pages
- 1326-1339
- ISSN
- 0018-9294 (ISSN-L)
- OpenAlex
- W2143459909
- Cited by
- 184
- References
- 1
- FWCI
- 7.77
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.