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ZENODO
Dataset . 2017
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2017
License: CC BY
Data sources: Datacite
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TROTS - The Radiotherapy Optimisation Test Set

Authors: Breedveld, Sebastiaan; Heijmen, Ben;

TROTS - The Radiotherapy Optimisation Test Set

Abstract

The Radiotherapy Optimisation Test Set (TROTS) is an extensive set of problems originating from radiotherapy (radiation therapy) treatment planning. This dataset is created for 2 purposes: (1) to supply a large-scale dense dataset to measure performance and quality of mathematical solvers, and (2) to supply a dataset to investigate the multi-criteria optimisation and decision-making nature of the radiotherapy problem. The dataset contains 120 problems (patients), divided over 6 different treatment protocols/tumour types. Each problem contains numerical data, a configuration for the optimisation problem, and data required to visualise and interpret the results. The data is stored as HDF5 compatible Matlab files, and includes scripts to work with the dataset. The set as present in this version is of date 13 May 2019. Updated versions of the Scripts and other extensions can be found at the following pages: Persistent page with links: Erasmus University Rotterdam Library Mirror project page: TROTS Mirror Main publication: S. Breedveld & B. Heijmen, Data for TROTS - The Radiotherapy Optimisation Test Set, Data in Brief 12 (2017) 143-149

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Keywords

Radiotherapy, Large-Scale Optimisation, Nonlinear optimisation, OR in health services, Multiple objective programming

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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