AI illuminates paths in oral cancer

transformative insights, diagnostic precision, and personalized strategies

Authors

  • Devesh U. Kapoor Dr. Dayaram Patel Pharmacy College, Bardoli-394601, Gujarat, India https://orcid.org/0000-0003-4085-8936
  • Pushpendra Kumar Saini Department of Pharmaceutics, Sri Balaji College of Pharmacy, Jaipur, Rajasthan-302013, India https://orcid.org/0009-0007-3127-365X
  • Narendra Sharma Department of Pharmaceutics, Sri Balaji College of Pharmacy, Jaipur, Rajasthan-302013, India https://orcid.org/0009-0001-8159-0668
  • Ankul Singh Faculty of Pharmacy, Department of Pharmacology, Dr MGR Educational and Research Institute, Velapanchavadi, Chennai-77, Tamil Nadu, India https://orcid.org/0000-0001-7927-0983
  • Bhupendra G. Prajapati Shree S. K. Patel College of Pharmaceutical Education and Research, Ganpat University, Kherva-384012, Gujarat, India. E-mail: bhupen27@gmail.com https://orcid.org/0000-0001-8242-4541
  • Gehan M. Elossaily Department of Basic Medical Sciences, College of Medicine, AlMaarefa University, P.O. Box 71666, Riyadh, 11597, Saudi Arabia https://orcid.org/0000-0003-3485-076X
  • Summya Rashid Department of Pharmacology & Toxicology, College of Pharmacy, Prince Sattam Bin Abdulaziz University, P.O. Box 173, Al-Kharj 11942, Saudi Arabia, E-mail: s.abdulrashid@psau.edu.sa https://orcid.org/0000-0002-7692-6059

DOI:

https://doi.org/10.17179/excli2024-7253

Keywords:

oral squamous cell carcinoma, machine learning, convolutional neural network, computed tomography

Abstract

Oral cancer retains one of the lowest survival rates worldwide, despite recent therapeutic advancements signifying a tenacious challenge in healthcare. Artificial intelligence exhibits noteworthy potential in escalating diagnostic and treatment procedures, offering promising advancements in healthcare. This review entails the traditional imaging techniques for the oral cancer treatment. The role of artificial intelligence in prognosis of oral cancer including predictive modeling, identification of prognostic factors and risk stratification also discussed significantly in this review. The review also encompasses the utilization of artificial intelligence such as automated image analysis, computer-aided detection and diagnosis integration of machine learning algorithms for oral cancer diagnosis and treatment. The customizing treatment approaches for oral cancer through artificial intelligence based personalized medicine is also part of this review.

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Published

2024-09-03

How to Cite

Kapoor, D. U., Saini, P. K., Sharma, N., Singh, A., Prajapati, B. G., Elossaily, G. M., & Rashid, S. (2024). AI illuminates paths in oral cancer: transformative insights, diagnostic precision, and personalized strategies. EXCLI Journal, 23, 1091–1116. https://doi.org/10.17179/excli2024-7253

Issue

Vol. 23 (2024)

Section

Review articles

Categories

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Copyright (c) 2024 Devesh U. Kapoor, Pushpendra Kumar Saini, Narendra Sharma, Ankul Singh, Bhupendra G. Prajapati, Gehan M. Elossaily, Summya Rashid

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