Application and Performance of Artificial Intelligence Technology in Oral Cancer Diagnosis and Prediction of Prognosis: A Systematic Review
Sanjeev B. Khanagar,
Sachin Naik,
Abdulaziz Abdullah Al Kheraif,
Satish Vishwanathaiah,
Prabhadevi C. Maganur,
Yaser Alhazmi,
Shazia Mushtaq,
Sachin C. Sarode,
Gargi S. Sarode,
Alessio Zanza,
Luca Testarelli,
Shankargouda Patil
Affiliations
Sanjeev B. Khanagar
Preventive Dental Science Department, College of Dentistry, King Saud Bin Abdulaziz University for Health Sciences, Riyadh 11481, Saudi Arabia
Sachin Naik
Dental Biomaterials Research Chair, Dental Health Department, College of Applied Medical Sciences, King Saud University, Riyadh 11433, Saudi Arabia
Abdulaziz Abdullah Al Kheraif
Dental Biomaterials Research Chair, Dental Health Department, College of Applied Medical Sciences, King Saud University, Riyadh 11433, Saudi Arabia
Satish Vishwanathaiah
Department of Preventive Dental Sciences, Division of Pedodontics, College of Dentistry, Jazan University, Jazan 45142, Saudi Arabia
Prabhadevi C. Maganur
Department of Preventive Dental Sciences, Division of Pedodontics, College of Dentistry, Jazan University, Jazan 45142, Saudi Arabia
Yaser Alhazmi
Department of Maxillofacial Surgery and Diagnostic Sciences, Division of Oral Pathology, College of Dentistry, Jazan University, Jazan 45142, Saudi Arabia
Shazia Mushtaq
College of Applied Medical Sciences, Dental Health Department, King Saud University, Riyadh 12372, Saudi Arabia
Sachin C. Sarode
Department of Oral and Maxillofacial Pathology, Dr. D.Y. Patil Dental College and Hospital, Dr. D. Y. Patil Vidyapeeth, Pimpri, Pune 411018, India
Gargi S. Sarode
Department of Oral and Maxillofacial Pathology, Dr. D.Y. Patil Dental College and Hospital, Dr. D. Y. Patil Vidyapeeth, Pimpri, Pune 411018, India
Alessio Zanza
Department of Maxillo and Oro-Facial Sciences, University of Rome La Sapienza, 00185 Rome, Italy
Luca Testarelli
Department of Maxillo and Oro-Facial Sciences, University of Rome La Sapienza, 00185 Rome, Italy
Shankargouda Patil
Department of Maxillofacial Surgery and Diagnostic Sciences, Division of Oral Pathology, College of Dentistry, Jazan University, Jazan 45142, Saudi Arabia
Oral cancer (OC) is a deadly disease with a high mortality and complex etiology. Artificial intelligence (AI) is one of the outstanding innovations in technology used in dental science. This paper intends to report on the application and performance of AI in diagnosis and predicting the occurrence of OC. In this study, we carried out data search through an electronic search in several renowned databases, which mainly included PubMed, Google Scholar, Scopus, Embase, Cochrane, Web of Science, and the Saudi Digital Library for articles that were published between January 2000 to March 2021. We included 16 articles that met the eligibility criteria and were critically analyzed using QUADAS-2. AI can precisely analyze an enormous dataset of images (fluorescent, hyperspectral, cytology, CT images, etc.) to diagnose OC. AI can accurately predict the occurrence of OC, as compared to conventional methods, by analyzing predisposing factors like age, gender, tobacco habits, and bio-markers. The precision and accuracy of AI in diagnosis as well as predicting the occurrence are higher than the current, existing clinical strategies, as well as conventional statistics like cox regression analysis and logistic regression.
