ORAL HEALTH OF AGRIBUSINESS WORKERS: CHALLENGES OF THE 2030 AGENDA AND ESG CRITERIA, PROMOTING WELL-BEING AND INCLUSION TO INCREASE PRODUCTIVITY

Abstract

Contemporary dentistry aims to replace private care with the sanitary model. Agribusiness workers have difficulties accessing dental services. The dental care system has difficulties in acquiring, updating, referring and monitoring patients. Artificial intelligence is a computer system that performs tasks that require human knowledge and skills such as recognizing patterns and images, understanding written and spoken open language, perceiving relationships/nexuses, following decision algorithms, understanding concepts, reasoning through the integration of new experiences by self-improvement. This research aims to demonstrate the importance of a convolutional network of dental data analysis that enables the diagnosis of different pathologies that may be found in agribusiness workers and the respective referral to the oral health recovery and control services of this target population. With the bibliometric review carried out, it was realized that the construction and wide use of convolutional networks in the different dental specialties can contribute to the improvement of primary oral health care, in the private network and especially in the public network, thus benefiting agribusiness workers with an increase in quality of life, oral health indices and indicators,  as well as in their productivity.

DOI:https://doi.org/10.56238/sevened2024.031-076