Prediction Models of Oral Diseases: A Systematic Review of the Literature

Dávila Olivos M.A.; Santos López F.M. · Lecture Notes in Networks and Systems (2024) · DOI: 10.1007/978-3-031-52255-0_22

Resumen

Oral diseases impose a significant burden on many countries, affecting individuals throughout their lives and causing pain, disfigurement, and even death. These diseases share similar risk factors with other important non-communicable diseases. In high-income countries, dental treatment accounts for 5% of healthcare expenditures and 20% of patient expenses. Unfortunately, low- and middle-income countries often struggle to afford preventive and treatment services for oral health disorders. Prediction models are crucial in optimizing resource allocation, particularly in environments where advanced sensing technologies foster healthier living conditions. In this context, this study conducts a systematic review to explore the applications and potential of artificial intelligence in addressing these challenges. This study aims to identify the solutions employed and the performance metrics used to assess their impact on public health, ultimately striving for improved outcomes. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Instituciones: Universidad Nacional Mayor de San Marcos