ArticleFrontiers in network physiology2026
Predictive modeling for cervical cancer: existing AI approaches and the emerging role of vaginal microbiome.
Article in Frontiers in network physiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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4 authors.
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Abstract
Cervical cancer remains a major global health burden, yet current screening tools lack precision in identifying which women with high-risk human papillomavirus (HPV) infection will progress to high-grade lesions or cancer. Within a network-physiology framework, cervical carcinogenesis is viewed as emerging from dynamic interactions between viral dynamics, host immunity, vaginal ecology, vaccination status and behaviour rather than from isolated risk factors. This perspective review examines artificial intelligence (AI) approaches for cervical cancer prediction and evaluates the emerging role of the vaginal microbiome as a complementary biomarker within these interconnected physiological networks. The review synthesises evidence linking non-Lactobacillus-dominated or
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