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Artificial Intelligence-based methods in head and neck cancer diagnosis : an overview

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Mahmood, Hanya, Shaban, Muhammad, Rajpoot, Nasir M. (Nasir Mahmood) and Khurram, Syed A (2021) Artificial Intelligence-based methods in head and neck cancer diagnosis : an overview. British Journal of Cancer, 124 . pp. 1934-1940. doi:10.1038/s41416-021-01386-x

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Official URL: http://dx.doi.org/10.1038/s41416-021-01386-x

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Abstract

Background:
This paper reviews recent literature employing Artificial Intelligence/Machine Learning (AI/ML) methods for diagnostic evaluation of head and neck cancers (HNC) using automated image analysis.

Methods:
Electronic database searches using MEDLINE via OVID, EMBASE and Google Scholar were conducted to retrieve articles using AI/ML for diagnostic evaluation of HNC (2009–2020). No restrictions were placed on the AI/ML method or imaging modality used.

Results:
In total, 32 articles were identified. HNC sites included oral cavity (n = 16), nasopharynx (n = 3), oropharynx (n = 3), larynx (n = 2), salivary glands (n = 2), sinonasal (n = 1) and in five studies multiple sites were studied. Imaging modalities included histological (n = 9), radiological (n = 8), hyperspectral (n = 6), endoscopic/clinical (n = 5), infrared thermal (n = 1) and optical (n = 1). Clinicopathologic/genomic data were used in two studies. Traditional ML methods were employed in 22 studies (69%), deep learning (DL) in eight studies (25%) and a combination of these methods in two studies (6%).

Conclusions:
There is an increasing volume of studies exploring the role of AI/ML to aid HNC detection using a range of imaging modalities. These methods can achieve high degrees of accuracy that can exceed the abilities of human judgement in making data predictions. Large-scale multi-centric prospective studies are required to aid deployment into clinical practice.

Item Type: Journal Article
Subjects: R Medicine > RC Internal medicine
Divisions: Faculty of Science > Computer Science
SWORD Depositor: Library Publications Router
Library of Congress Subject Headings (LCSH): Head -- Cancer -- Diagnosis -- , Neck -- Cancer -- Diagnosis -- , Head -- Cancer -- Imaging , Neck -- Cancer -- Imaging , Diagnostic imaging -- Digital techniques
Journal or Publication Title: British Journal of Cancer
Publisher: Nature Publishing Group
ISSN: 0007-0920
Official Date: 19 April 2021
Dates:
DateEvent
19 April 2021Published
31 March 2021Accepted
Volume: 124
Page Range: pp. 1934-1940
DOI: 10.1038/s41416-021-01386-x
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
UNSPECIFIED[NIHR] National Institute for Health Researchhttp://dx.doi.org/10.13039/501100000272
UNSPECIFIEDSheffield Hospitals Charityhttp://dx.doi.org/10.13039/501100004876
18181UK Research and Innovationhttp://dx.doi.org/10.13039/100014013
MR/P015476/1[MRC] Medical Research Councilhttp://dx.doi.org/10.13039/501100000265
UNSPECIFIEDAlan Turing Institutehttp://dx.doi.org/10.13039/100012338

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