dc.contributor.author |
Malherbe, Kathryn
|
|
dc.date.accessioned |
2022-02-08T07:05:17Z |
|
dc.date.issued |
2021-08 |
|
dc.description.abstract |
A critical knowledge gap has been noted in breast cancer detection, prognosis, and evaluation between tumor microenvironment and associated neoplasm. Artificial intelligence (AI) has multiple subsets or methods for data extraction and evaluation, including artificial neural networking, which allows computational foundations, similar to neurons, to make connections and new neural pathways during data set training. Deep machine learning and AI hold great potential to accurately assess tumor microenvironment models employing vast data management techniques. Despite the significant potential AI holds, there is still much debate surrounding the appropriate and ethical curation of medical data from picture archiving and communication systems. AI output's clinical significance depends on its human predecessor's data training sets. Integration between biomarkers, risk factors, and imaging data will allow the best predictor models for patient-based outcomes. |
en_ZA |
dc.description.department |
Radiography |
en_ZA |
dc.description.embargo |
2022-08-01 |
|
dc.description.librarian |
hj2022 |
en_ZA |
dc.description.uri |
https://ajp.amjpathol.org |
en_ZA |
dc.identifier.citation |
Malherbe, K. 2021, 'Tumor microenvironment and the role of artificial intelligence in breast cancer detection and prognosis', American Journal of Pathology, vol. 191, no. 8, pp. 1364-1373. |
en_ZA |
dc.identifier.issn |
0002-9440 (print) |
|
dc.identifier.issn |
1525-2191 (online) |
|
dc.identifier.other |
10.1016/j.ajpath.2021.01.014 |
|
dc.identifier.uri |
http://hdl.handle.net/2263/83663 |
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dc.language.iso |
en |
en_ZA |
dc.publisher |
Elsevier |
en_ZA |
dc.rights |
©2021 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved. Notice : this is the author’s version of a work that was accepted for publication in American Journal of Pathology. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. A definitive version was subsequently published in American Journal of Pathology, vol. 191, no. 8, pp. 1364-1373, 2021. doi : 10.1016/j.ajpath.2021.01.014. |
en_ZA |
dc.subject |
Breast cancer |
en_ZA |
dc.subject |
Detection |
en_ZA |
dc.subject |
Prognosis |
en_ZA |
dc.subject |
Tumor microenvironment (TME) |
en_ZA |
dc.subject |
Artificial intelligence (AI) |
en_ZA |
dc.subject |
Extracellular matrix (ECM) |
en_ZA |
dc.subject |
Immune cells |
en_ZA |
dc.title |
Tumor microenvironment and the role of artificial intelligence in breast cancer detection and prognosis |
en_ZA |
dc.type |
Postprint Article |
en_ZA |