Advancing Cervical Cancer Management with Artificial Intelligence Current Perspectives and Future Trends

Background: The field of cervical cancer care has been revolutionized by artificial
intelligence (AI), enabling advanced analysis of imaging and multi-omics data, and leading
to more accurate diagnosis, improved prediction of patient outcomes, and support for
personalized treatments.
Procedure: This systematic review complies with the Preferred Reporting Items for
Systematic Reviews and Meta-Analyses (PRISMA) and uses the PRISMA checklist. A
comprehensive literature search was conducted using the databases of Web of Science,
Scopus, IEEE, and PubMed to identify the characteristics of studies published between 2021
and 2026. Published literature were assessed for eligibility as long-form (original and
review articles) relating to AI use for screening, diagnosis, prognosis, radiomics, pathology,
and clinical decision support in relation to cervical cancer. All data synthesized were
qualitative.
Results: AI-based models enable accurate identification and classification of cervical
neoplasia. They also facilitate earlier diagnosis through automated feature extraction from
imaging. AI-assisted frameworks are beginning to support the development of precision
medicine treatments tailored to individuals.
Discussion: The clinical translation of AI into practice faces challenges such as data
heterogeneity, insufficient external validation, and a lack of model interpretability. To
address these, creating standardized datasets and developing interdisciplinary
collaborations will enhance AI adoption in clinical practice.

Conclusion: There is substantial potential for AI to provide improved cervical cancer care.
Future initiatives to facilitate this include creating well-validated, standardized datasets and
clinically interpretable models to ensure the successful implementation of AI in practice in
the real world.