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QIN Benchmarks for Clinical Translation of Quantitative Imaging Tools
The Quantitative Imaging Network of the National Cancer Institute is in its 10th year of operation, and research teams within the network are developing and validating clinical decision support software tools to measure or predict the response of cancers to various therapies. As projects progress fr...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Grapho Publications, LLC
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6403038/ https://www.ncbi.nlm.nih.gov/pubmed/30854436 http://dx.doi.org/10.18383/j.tom.2018.00045 |
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author | Farahani, Keyvan Tata, Darrell Nordstrom, Robert J. |
author_facet | Farahani, Keyvan Tata, Darrell Nordstrom, Robert J. |
author_sort | Farahani, Keyvan |
collection | PubMed |
description | The Quantitative Imaging Network of the National Cancer Institute is in its 10th year of operation, and research teams within the network are developing and validating clinical decision support software tools to measure or predict the response of cancers to various therapies. As projects progress from development activities to validation of quantitative imaging tools and methods, it is important to evaluate the performance and clinical readiness of the tools before committing them to prospective clinical trials. A variety of tests, including special challenges and tool benchmarking, have been instituted within the network to prepare the quantitative imaging tools for service in clinical trials. This article highlights the benchmarking process and provides a current evaluation of several tools in their transition from development to validation. |
format | Online Article Text |
id | pubmed-6403038 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Grapho Publications, LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-64030382019-03-08 QIN Benchmarks for Clinical Translation of Quantitative Imaging Tools Farahani, Keyvan Tata, Darrell Nordstrom, Robert J. Tomography Perspectives The Quantitative Imaging Network of the National Cancer Institute is in its 10th year of operation, and research teams within the network are developing and validating clinical decision support software tools to measure or predict the response of cancers to various therapies. As projects progress from development activities to validation of quantitative imaging tools and methods, it is important to evaluate the performance and clinical readiness of the tools before committing them to prospective clinical trials. A variety of tests, including special challenges and tool benchmarking, have been instituted within the network to prepare the quantitative imaging tools for service in clinical trials. This article highlights the benchmarking process and provides a current evaluation of several tools in their transition from development to validation. Grapho Publications, LLC 2019-03 /pmc/articles/PMC6403038/ /pubmed/30854436 http://dx.doi.org/10.18383/j.tom.2018.00045 Text en © 2019 The Authors. Published by Grapho Publications, LLC http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Perspectives Farahani, Keyvan Tata, Darrell Nordstrom, Robert J. QIN Benchmarks for Clinical Translation of Quantitative Imaging Tools |
title | QIN Benchmarks for Clinical Translation of Quantitative Imaging Tools |
title_full | QIN Benchmarks for Clinical Translation of Quantitative Imaging Tools |
title_fullStr | QIN Benchmarks for Clinical Translation of Quantitative Imaging Tools |
title_full_unstemmed | QIN Benchmarks for Clinical Translation of Quantitative Imaging Tools |
title_short | QIN Benchmarks for Clinical Translation of Quantitative Imaging Tools |
title_sort | qin benchmarks for clinical translation of quantitative imaging tools |
topic | Perspectives |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6403038/ https://www.ncbi.nlm.nih.gov/pubmed/30854436 http://dx.doi.org/10.18383/j.tom.2018.00045 |
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