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A Software Application for Mining and Presenting Relevant Cancer Clinical Trials per Cancer Mutation
ClinicalTrials.org is a popular portal which physicians use to find clinical trials for their patients. However, the current setup of ClinicalTrials.org makes it difficult for oncologists to locate clinical trials for patients based on mutational status. We present CTMine, a system that mines Clinic...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5485907/ https://www.ncbi.nlm.nih.gov/pubmed/28690394 http://dx.doi.org/10.1177/1176935117711940 |
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author | Gandy, Lisa M Gumm, Jordan Blackford, Amanda L Fertig, Elana J Diaz, Luis A |
author_facet | Gandy, Lisa M Gumm, Jordan Blackford, Amanda L Fertig, Elana J Diaz, Luis A |
author_sort | Gandy, Lisa M |
collection | PubMed |
description | ClinicalTrials.org is a popular portal which physicians use to find clinical trials for their patients. However, the current setup of ClinicalTrials.org makes it difficult for oncologists to locate clinical trials for patients based on mutational status. We present CTMine, a system that mines ClinicalTrials.org for clinical trials per cancer mutation and displays the trials in a user-friendly Web application. The system currently lists clinical trials for 6 common genes (ALK, BRAF, ERBB2, EGFR, KIT, and KRAS). The current machine learning model used to identify relevant clinical trials focusing on the above gene mutations had an average 88% precision/recall. As part of this analysis, we compared human versus machine and found that oncologists were unable to reach a consensus on whether a clinical trial mined by CTMine was “relevant” per gene mutation, a finding that highlights an important topic which deems future exploration. |
format | Online Article Text |
id | pubmed-5485907 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-54859072017-07-07 A Software Application for Mining and Presenting Relevant Cancer Clinical Trials per Cancer Mutation Gandy, Lisa M Gumm, Jordan Blackford, Amanda L Fertig, Elana J Diaz, Luis A Cancer Inform Original Research ClinicalTrials.org is a popular portal which physicians use to find clinical trials for their patients. However, the current setup of ClinicalTrials.org makes it difficult for oncologists to locate clinical trials for patients based on mutational status. We present CTMine, a system that mines ClinicalTrials.org for clinical trials per cancer mutation and displays the trials in a user-friendly Web application. The system currently lists clinical trials for 6 common genes (ALK, BRAF, ERBB2, EGFR, KIT, and KRAS). The current machine learning model used to identify relevant clinical trials focusing on the above gene mutations had an average 88% precision/recall. As part of this analysis, we compared human versus machine and found that oncologists were unable to reach a consensus on whether a clinical trial mined by CTMine was “relevant” per gene mutation, a finding that highlights an important topic which deems future exploration. SAGE Publications 2017-06-22 /pmc/articles/PMC5485907/ /pubmed/28690394 http://dx.doi.org/10.1177/1176935117711940 Text en © The Author(s) 2017 This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page(https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Original Research Gandy, Lisa M Gumm, Jordan Blackford, Amanda L Fertig, Elana J Diaz, Luis A A Software Application for Mining and Presenting Relevant Cancer Clinical Trials per Cancer Mutation |
title | A Software Application for Mining and Presenting Relevant Cancer Clinical Trials per Cancer Mutation |
title_full | A Software Application for Mining and Presenting Relevant Cancer Clinical Trials per Cancer Mutation |
title_fullStr | A Software Application for Mining and Presenting Relevant Cancer Clinical Trials per Cancer Mutation |
title_full_unstemmed | A Software Application for Mining and Presenting Relevant Cancer Clinical Trials per Cancer Mutation |
title_short | A Software Application for Mining and Presenting Relevant Cancer Clinical Trials per Cancer Mutation |
title_sort | software application for mining and presenting relevant cancer clinical trials per cancer mutation |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5485907/ https://www.ncbi.nlm.nih.gov/pubmed/28690394 http://dx.doi.org/10.1177/1176935117711940 |
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