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Integrating pathomics with radiomics and genomics for cancer prognosis: A brief review

In the last decade, the focus of computational pathology research community has shifted from replicating the pathological examination for diagnosis done by pathologists to unlocking and discovering “sub-visual” prognostic image cues from the histopathological image. While we are getting more knowled...

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Detalles Bibliográficos
Autores principales: Lu, Cheng, Shiradkar, Rakesh, Liu, Zaiyi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8580801/
https://www.ncbi.nlm.nih.gov/pubmed/34815630
http://dx.doi.org/10.21147/j.issn.1000-9604.2021.05.03
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author Lu, Cheng
Shiradkar, Rakesh
Liu, Zaiyi
author_facet Lu, Cheng
Shiradkar, Rakesh
Liu, Zaiyi
author_sort Lu, Cheng
collection PubMed
description In the last decade, the focus of computational pathology research community has shifted from replicating the pathological examination for diagnosis done by pathologists to unlocking and discovering “sub-visual” prognostic image cues from the histopathological image. While we are getting more knowledge and experience in digital pathology, the emerging goal is to integrate other-omics or modalities that will contribute for building a better prognostic assay. In this paper, we provide a brief review of representative works that focus on integrating pathomics with radiomics and genomics for cancer prognosis. It includes: correlation of pathomics and genomics; fusion of pathomics and genomics; fusion of pathomics and radiomics. We also present challenges, potential opportunities, and avenues for future work.
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spelling pubmed-85808012021-11-22 Integrating pathomics with radiomics and genomics for cancer prognosis: A brief review Lu, Cheng Shiradkar, Rakesh Liu, Zaiyi Chin J Cancer Res Review Article In the last decade, the focus of computational pathology research community has shifted from replicating the pathological examination for diagnosis done by pathologists to unlocking and discovering “sub-visual” prognostic image cues from the histopathological image. While we are getting more knowledge and experience in digital pathology, the emerging goal is to integrate other-omics or modalities that will contribute for building a better prognostic assay. In this paper, we provide a brief review of representative works that focus on integrating pathomics with radiomics and genomics for cancer prognosis. It includes: correlation of pathomics and genomics; fusion of pathomics and genomics; fusion of pathomics and radiomics. We also present challenges, potential opportunities, and avenues for future work. AME Publishing Company 2021-10-31 /pmc/articles/PMC8580801/ /pubmed/34815630 http://dx.doi.org/10.21147/j.issn.1000-9604.2021.05.03 Text en Copyright ©2021Chinese Journal of Cancer Research. All rights reserved. https://creativecommons.org/licenses/by-nc-sa/4.0/This work is licensed under a Creative Commons Attribution-Non Commercial-Share Alike 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/4.0/ (https://creativecommons.org/licenses/by-nc-sa/4.0/)
spellingShingle Review Article
Lu, Cheng
Shiradkar, Rakesh
Liu, Zaiyi
Integrating pathomics with radiomics and genomics for cancer prognosis: A brief review
title Integrating pathomics with radiomics and genomics for cancer prognosis: A brief review
title_full Integrating pathomics with radiomics and genomics for cancer prognosis: A brief review
title_fullStr Integrating pathomics with radiomics and genomics for cancer prognosis: A brief review
title_full_unstemmed Integrating pathomics with radiomics and genomics for cancer prognosis: A brief review
title_short Integrating pathomics with radiomics and genomics for cancer prognosis: A brief review
title_sort integrating pathomics with radiomics and genomics for cancer prognosis: a brief review
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8580801/
https://www.ncbi.nlm.nih.gov/pubmed/34815630
http://dx.doi.org/10.21147/j.issn.1000-9604.2021.05.03
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