Artificial Intelligence-based methods in head and neck cancer diagnosis: an overview.
Br J Cancer
; 124(12): 1934-1940, 2021 06.
Article
en En
| MEDLINE
| ID: mdl-33875821
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.
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Procesamiento de Imagen Asistido por Computador
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Inteligencia Artificial
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Neoplasias de Cabeza y Cuello
Tipo de estudio:
Clinical_trials
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Diagnostic_studies
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Observational_studies
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Prognostic_studies
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Risk_factors_studies
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Systematic_reviews
Límite:
Humans
Idioma:
En
Año:
2021
Tipo del documento:
Article