A Systematic Analysis of Artificial Intelligence in Dentistry


  • Kashif Adnan Registrar de'Montmorency College of Dentistry, Lahore. Pakistan.
  • Muhammad Kaleem Khan Resident (Oral Surgery) Karachi Medical and Dental College, Karachi, Pakistan.
  • Madiha Umar Dental Materials NUMS, Rawalpindi, Pakistan.
  • Muhammad Umair Faculty of Allied Health Sciences, Gomal University, Dera Ismail Khan, Pakistan.


Artificial Intelligence, Dentistry, Healthcare


Artificial intelligence (AI) has emerged as a transformative technology in various domains, and dentistry is no exception. This paper explores the applications and implications of AI in dentistry, highlighting its potential to revolutionize dental practices, enhance patient care, and improve treatment outcomes. The population of interest for this study comprises dental practitioners, researchers, and patients involved in dental care. Dentists are increasingly recognizing the value of AI in streamlining various tasks, such as diagnosis, treatment planning, and patient management. AI algorithms can analyze radiographic images, intraoral scans, and clinical data to assist in detecting and classifying dental diseases, including caries, periodontal conditions, and oral cancers. By leveraging machine learning techniques, AI systems can provide accurate and timely diagnoses, aiding dentists in making informed decisions and improving treatment efficacy. Sampling for this study involves selecting a representative sample of dental professionals from diverse geographical regions, ranging from general dentists to specialists, to comprehensively understand their perspectives and experiences with AI in dentistry. Patients receiving dental care were also included in the sample to gauge their perceptions of AI technologies and their impact on the quality of care received. The sampling technique employed was a combination of convenience sampling and purposive sampling. Convenience sampling was used to select dental practitioners from various dental clinics, hospitals, and academic institutions. Purposive sampling was employed to identify patients who have been exposed to AI-based dental technologies. The sample size was determined based on data saturation, ensuring sufficient diversity and representation within the study. By examining the population and employing a well-designed sampling strategy, this study aims to provide valuable insights into AI's current adoption and future potential in dentistry. The findings contribute to the existing literature on AI in healthcare and help guide future research, policy-making, and implementation strategies in the dental field.




How to Cite

Kashif Adnan, Muhammad Kaleem Khan, Madiha Umar, & Muhammad Umair. (2023). A Systematic Analysis of Artificial Intelligence in Dentistry. Journal of Computing & Biomedical Informatics, 5(01), 74–81. Retrieved from https://jcbi.org/index.php/Main/article/view/167