AI-based automated system enhances performance in dentistry: Study
The performance of an AI-based automated system is excellent in dentistry, suggests a study published in the Journal of Dental Sciences.
Artificial intelligence (AI) has made deep inroads into dentistry in the last few years. A group of researchers from Saudi Arabia and India conducted a study to identify the development of AI applications that are widely employed in dentistry and evaluate their performance in terms of diagnosis, clinical decision-making, and predicting the prognosis of the treatment.
The literature for this paper was identified and selected by performing a thorough search in electronic databases like PubMed, Medline, Embase, Cochrane, Google Scholar, Scopus, Web of science, and Saudi digital library published over the past two decades. After applying inclusion and exclusion criteria, 43 articles were read in full and critically analyzed. Quality analysis was performed using QUADAS-2.
The results of the study are as follows:
· AI technologies are widely implemented in a wide range of dentistry specialities.
· Most of the documented work is focused on AI models that rely on convolutional neural networks (CNNs) and artificial neural networks (ANNs).
· These AI models have been used in detection and diagnosis of dental caries, vertical root fractures, apical lesions, salivary gland diseases, maxillary sinusitis, maxillofacial cysts, cervical lymph nodes metastasis, osteoporosis, cancerous lesions, alveolar bone loss, predicting orthodontic extractions, need for orthodontic treatments, cephalometric analysis, age and gender determination.
Thus, the researchers concluded that the performance of an AI-based automated system is excellent. They mimic the precision and accuracy of trained specialists; in some studies, it was found that these systems were even able to outmatch dental specialists in terms of performance and accuracy.
Reference:
Developments, application, and performance of artificial intelligence in dentistry – A systematic review by Khanagar S et. al published in the Journal of Dental Sciences.
https://doi.org/10.1016/j.jds.2020.06.019
