A Crosstalk Between Periodontal Disease and Human Immunodeficiency Virus: Application of Artificial Intelligence and Machine Learning in Risk Assessment and Diagnosis—A Narrative Review

Periodontal disease (PD) is an inflammatory condition caused by multiple periodontal pathogens, particularly those belonging to the Red Complex. Various risk factors influence the development of PD, including age, sex, socioeconomic status, ethnicity, and underlying health issues. Numerous molecular and cellular processes govern the inflammatory response, which affects the gums and tooth-supporting structures and ultimately leads to alveolar bone loss. Accumulating evidence suggests that Human Immunodeficiency Virus-1 (HIV-1) infection significantly impacts the initiation and progression of PD. While HIV-1 is treated with antiretroviral therapy, this treatment can also affect the course of periodontal disease and systemic health status. AI/ML and precision medicine integrates genomic and computational data to enable individualized disease prevention and treatment strategies. When applied responsibly, these technologies can assist clinicians in the timely detection of both PD and HIV-1. This review aims to discuss the factors that exacerbate PD and the available therapeutic options for persons living with (PLWH) and without HIV-1. Additionally, we emphasize the need for developing biomarkers for early diagnosis and intervention to manage PD effectively, ultimately improving the quality of life for those living with HIV.