Integrating Psychoneuroimmunological Factors into AI-Driven Risk Stratification for Cervical Intraepithelial Neoplasia:A Mixed Bibliometric and Empirical Study from Northern Romania Focusing on Depression and Anxiety

Abstract

Cervical intraepithelial neoplasia (CIN) is a multifactorial pathology mainly determined by persistent infection with high-risk human papillomavirus (HPV) genotypes and modulated by both immunological and psychological factors. This mixed bibliometric and empirical study integrates psychoneuroimmunological concepts with clinical data from a cohort of 150 patients (aged 18–55 years) from northern Romania. Seventy percent tested positive for high-risk HPV by self-sampling and all completed the PHQ-9 and GAD-7 scales that were subsequently assessed. Symptoms of depression and anxiety were prevalent, with anxiety being reported by 43% of participants who performed self-sampling at home.Fifty women with cytologically diagnosed HSIL underwent a comparative evaluation using both, classical colposcopy and the artificial intelligence-assisted EVA system (MobileODT, Israel). Artificial intelligence-based colposcopy demonstrated higher sensitivity (92% versus 82%) and higher diagnostic concordance (88%) with histopathological confirmation, suggesting superior accuracy and clinical feasibility.These results support the integration of psychoneuroimmunological and artificial intelligence-assisted diagnostic parameters into cervical cancer prevention frameworks, highlighting the importance through which artificial intelligence could complement neoplasia prevention, addressing psychological profile and biological markers to improve personalised risk stratification.