AI a valuable diagnostic tool for detection of Oral Cancer in early stages

The early detection of oral cancer (OC) at the earliest stage significantly increases survival rates. Recently, there has been an increasing interest in the use of artificial intelligence (AI) technologies in diagnostic medicine. This study aimed to critically analyse the available evidence concerning the utility of AI in the diagnosis of oral cancer. Special consideration was given to the diagnostic accuracy of AI and its ability to identify the early stages of oral cancer.

From the date of inception to December 2021, 4 databases (PubMed, Scopus, EBSCO, and OVID) were searched. Three independent authors selected studies on the basis of strict inclusion criteria. The risk of bias and applicability were assessed using the prediction model risk of the bias assessment tool. Of the 606 initial records, 17 studies with a total of 7245 patients and 69,425 images were included. Ten statistical methods were used to assess AI performance in the included studies. Six studies used supervised machine learning, whilst 11 used deep learning. The results of deep learning ranged from accuracy of 81% to 99.7%, sensitivity 79% to 98.75%, specificity 82% to 100%, and area under the curve (AUC) 79% to 99.5%.

Results:

Results obtained from supervised machine learning demonstrated an accuracy ranging from 43.5% to 100%, sensitivity of 94% to 100%, specificity 16% to 100%, and AUC of 93%.

Thus, there is no clear consensus regarding the best AI method for oral cancer detection. AI is a valuable diagnostic tool that represents a large evolutionary leap in the detection of oral cancer in its early stages. Based on the evidence, deep learning, such as a deep convolutional neural network, is more accurate in the early detection of oral cancer compared to supervised machine learning.

Reference:

Natheer Al-Rawi, Afrah Sultan, Batool Rajai, Haneen Shuaeeb, Mariam Alnajjar, Maryam Alketbi, Yara Mohammad, Shishir Ram Shetty, Mubarak Ahmed Mashrah, The Effectiveness of Artificial Intelligence in Detection of Oral Cancer, International Dental Journal, Volume 72, Issue 4, 2022,Pages 436-447, ISSN 0020-6539, https://doi.org/10.1016/j.identj.2022.03.001

Keywords:

Natheer Al-Rawi, Afrah Sultan, Batool Rajai, Haneen Shuaeeb, Mariam Alnajjar, Maryam Alketbi, Yara Mohammad, Shishir Ram Shetty, Mubarak Ahmed Mashrah, The Effectiveness of Artificial Intelligence in Detection of Oral Cancer, International Dental Journal,