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Cancer Informatics in 2018: The Mysteries of the Cancer Genome Continue to Unravel, Deep Learning Approaches the Clinic, and Passive Data Collection Demonstrates Utility
Objective : To summarize significant research contributions on cancer informatics published in 2018. Methods : An extensive search using PubMed/Medline, Google Scholar, and manual review was conducted to identify the scientific contributions published in 2018 that address topics in cancer informatic...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Georg Thieme Verlag KG
2019
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6697504/ https://www.ncbi.nlm.nih.gov/pubmed/31419838 http://dx.doi.org/10.1055/s-0039-1677931 |
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author | Warner, Jeremy L. Patt, Debra |
author_facet | Warner, Jeremy L. Patt, Debra |
author_sort | Warner, Jeremy L. |
collection | PubMed |
description | Objective : To summarize significant research contributions on cancer informatics published in 2018. Methods : An extensive search using PubMed/Medline, Google Scholar, and manual review was conducted to identify the scientific contributions published in 2018 that address topics in cancer informatics. The selection process comprised three steps: (i) 15 candidate best papers were first selected by the two section editors, (ii) external reviewers from internationally renowned research teams reviewed each candidate best paper, and (iii) the final selection of four best papers was conducted by the editorial board of the International Medical Informatics Association (IMIA) Yearbook. Results : The four selected best papers present studies addressing many facets of cancer informatics, with immediate applicability in the translational and clinical domains. Conclusion : Cancer informatics is a broad and vigorous subfield of biomedical informatics. Progress in cancer genomics, artificial intelligence, and passively collected data is especially notable in 2018. |
format | Online Article Text |
id | pubmed-6697504 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Georg Thieme Verlag KG |
record_format | MEDLINE/PubMed |
spelling | pubmed-66975042019-08-19 Cancer Informatics in 2018: The Mysteries of the Cancer Genome Continue to Unravel, Deep Learning Approaches the Clinic, and Passive Data Collection Demonstrates Utility Warner, Jeremy L. Patt, Debra Yearb Med Inform Objective : To summarize significant research contributions on cancer informatics published in 2018. Methods : An extensive search using PubMed/Medline, Google Scholar, and manual review was conducted to identify the scientific contributions published in 2018 that address topics in cancer informatics. The selection process comprised three steps: (i) 15 candidate best papers were first selected by the two section editors, (ii) external reviewers from internationally renowned research teams reviewed each candidate best paper, and (iii) the final selection of four best papers was conducted by the editorial board of the International Medical Informatics Association (IMIA) Yearbook. Results : The four selected best papers present studies addressing many facets of cancer informatics, with immediate applicability in the translational and clinical domains. Conclusion : Cancer informatics is a broad and vigorous subfield of biomedical informatics. Progress in cancer genomics, artificial intelligence, and passively collected data is especially notable in 2018. Georg Thieme Verlag KG 2019-08 2019-08-16 /pmc/articles/PMC6697504/ /pubmed/31419838 http://dx.doi.org/10.1055/s-0039-1677931 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License, which permits unrestricted reproduction and distribution, for non-commercial purposes only; and use and reproduction, but not distribution, of adapted material for non-commercial purposes only, provided the original work is properly cited. |
spellingShingle | Warner, Jeremy L. Patt, Debra Cancer Informatics in 2018: The Mysteries of the Cancer Genome Continue to Unravel, Deep Learning Approaches the Clinic, and Passive Data Collection Demonstrates Utility |
title | Cancer Informatics in 2018: The Mysteries of the Cancer Genome Continue to Unravel, Deep Learning Approaches the Clinic, and Passive Data Collection Demonstrates Utility |
title_full | Cancer Informatics in 2018: The Mysteries of the Cancer Genome Continue to Unravel, Deep Learning Approaches the Clinic, and Passive Data Collection Demonstrates Utility |
title_fullStr | Cancer Informatics in 2018: The Mysteries of the Cancer Genome Continue to Unravel, Deep Learning Approaches the Clinic, and Passive Data Collection Demonstrates Utility |
title_full_unstemmed | Cancer Informatics in 2018: The Mysteries of the Cancer Genome Continue to Unravel, Deep Learning Approaches the Clinic, and Passive Data Collection Demonstrates Utility |
title_short | Cancer Informatics in 2018: The Mysteries of the Cancer Genome Continue to Unravel, Deep Learning Approaches the Clinic, and Passive Data Collection Demonstrates Utility |
title_sort | cancer informatics in 2018: the mysteries of the cancer genome continue to unravel, deep learning approaches the clinic, and passive data collection demonstrates utility |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6697504/ https://www.ncbi.nlm.nih.gov/pubmed/31419838 http://dx.doi.org/10.1055/s-0039-1677931 |
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