The contribution of artificial intelligence to reducing the diagnostic delay in oral cancer

Küçük Resim Yok

Tarih

2021

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

Elsevier

Erişim Hakkı

info:eu-repo/semantics/openAccess

Özet

Oral cancer (OC) is the sixth most commonly reported malignant disease globally, with high rates of diseaserelated morbidity and mortality due to advanced loco-regional stage at diagnosis. Early detection and prompt treatment offer the best outcomes to patients, yet the majority of OC lesions are detected at late stages with 45% survival rate for 2 years. The primary cause of poor OC outcomes is unavailable or ineffective screening and surveillance at the local point-of-care level, leading to delays in specialist referral and subsequent treatment. Lack of adequate awareness of OC among the public and professionals, and barriers to accessing health care services in a timely manner also contribute to delayed diagnosis. As image analysis and diagnostic technologies are evolving, various artificial intelligence (AI) approaches, specific algorithms and predictive models are beginning to have a considerable impact in improving diagnostic accuracy for OC. AI based technologies combined with intraoral photographic images or optical imaging methods are under investigation for automated detection and classification of OC. These new methods and technologies have great potential to improve outcomes, especially in low-resource settings. Such approaches can be used to predict oral cancer risk as an adjunct to population screening by providing real-time risk assessment. The objective of this study is to (1) provide an overview of components of delayed OC diagnosis and (2) evaluate novel AI based approaches with respect to their utility and implications for improving oral cancer detection.

Açıklama

Anahtar Kelimeler

Artificial intelligence, Oral cancer, Early detection, Oral cancer diagnosis, Diagnostic delay, Squamous-Cell Carcinoma, Neural-Network, Neck-Cancer, Classification, Head, Spectra, Cavity, Health, Stage, Risk

Kaynak

Oral Oncology

WoS Q Değeri

Q1

Scopus Q Değeri

Cilt

116

Sayı

Künye