Elektrina, Oktaliza
Progam Studi Kebidanan, Fakultas Ilmu Kesehatan, Universitas Riau Indonesia

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Transformasi Teknologi Deteksi Dini Kanker Serviks: Studi Bibliometrik Mengenai Pergeseran dari Metode Konvensional ke Kecerdasan Buatan Okrianti, Surisna; Elektrina, Oktaliza; Romlah, Siti; Farizal, Ekry Binti; Ilmaskal, Radian
JUMANTIK (Jurnal Ilmiah Penelitian Kesehatan) Vol 11, No 1 (2026)
Publisher : Prodi Kesehatan Masyarakat Fakultas Kesehatan Masyarakat UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/jumantik.v11i1.28743

Abstract

Cervical cancer is a critical global health urgency driving the WHO's elimination agenda. Concurrently, early detection is shifting from conventional Pap smears to molecular HPV DNA testing and Artificial Intelligence (AI). To address the research gap in comprehensively mapping this technological transition, this study analyzed the global evolution of cervical cancer early detection from 2015 to 2025 using a bibliometric approach. Following PRISMA guidelines, we retrieved 11,410 English-language articles and reviews from the Scopus database. Data were analyzed using Biblioshiny and VOSviewer. Results indicate a 202.29% increase in publications, predominantly led by the United States and China. Thematic shifts highlight a clear transition toward AI, machine learning, and deep learning to enhance diagnostic accuracy. However, challenges in data quality, clinical validation, and system integration persist. Ultimately, these findings provide actionable evidence for health policymakers to formulate effective, technology-driven screening strategies and guide researchers in addressing bottlenecks to safely integrate AI into real-world clinical workflows.