Literature DB >> 32162398

Improvement of oral cancer screening quality and reach: The promise of artificial intelligence.

Ankita Kar1, Volkert B Wreesmann2, Vineeth Shwetha3, Shalini Thakur1, Vishal U S Rao1, Gururaj Arakeri4, Peter A Brennan5.   

Abstract

Oral cancer is easily detectable by physical (self) examination. However, many cases of oral cancer are detected late, which causes unnecessary morbidity and mortality. Screening of high-risk populations seems beneficial, but these populations are commonly located in regions with limited access to health care. The advent of information technology and its modern derivative artificial intelligence (AI) promises to improve oral cancer screening but to date, few efforts have been made to apply these techniques and relatively little research has been conducted to retrieve meaningful information from AI data. In this paper, we discuss the promise of AI to improve the quality and reach of oral cancer screening and its potential effect on improving mortality and unequal access to health care around the world.
© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Entities:  

Keywords:  artificial intelligence; early detection; machine learning; oral squamous cell carcinoma

Mesh:

Year:  2020        PMID: 32162398     DOI: 10.1111/jop.13013

Source DB:  PubMed          Journal:  J Oral Pathol Med        ISSN: 0904-2512            Impact factor:   4.253


  4 in total

Review 1.  The contribution of artificial intelligence to reducing the diagnostic delay in oral cancer.

Authors:  Betul Ilhan; Pelin Guneri; Petra Wilder-Smith
Journal:  Oral Oncol       Date:  2021-03-09       Impact factor: 5.337

Review 2.  The Effectiveness of Semi-Automated and Fully Automatic Segmentation for Inferior Alveolar Canal Localization on CBCT Scans: A Systematic Review.

Authors:  Julien Issa; Raphael Olszewski; Marta Dyszkiewicz-Konwińska
Journal:  Int J Environ Res Public Health       Date:  2022-01-04       Impact factor: 3.390

3.  Evaluation of YouTube Videos as a Source of Information About Oral Self-examination to Detect Oral Cancer and Precancerous Lesions.

Authors:  Nitin D Gulve; Pallavi R Tripathi; Sachinkumar D Dahivelkar; Meenal N Gulve; Reeya N Gulve; Swapnil J Kolhe
Journal:  J Int Soc Prev Community Dent       Date:  2022-04-08

4.  Landmark annotation and mandibular lateral deviation analysis of posteroanterior cephalograms using a convolutional neural network.

Authors:  Saori Takeda; Yuichi Mine; Yuki Yoshimi; Shota Ito; Kotaro Tanimoto; Takeshi Murayama
Journal:  J Dent Sci       Date:  2020-11-11       Impact factor: 2.080

  4 in total

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