AI-based early detection of cervical cancer: A new hope for cancer prevention in indonesia - Taufiq Qul Hidayat; Dwi Andhika Farzani Husain (Indonesian Public Health-Observer Information Forum (IPHORR) Kerjasama dengan Persatuan Perawat Nasional Indonesia (PPNI), 2025)
Background: Cervical cancer is one of the leading causes of death among women in Indonesia, mostly due to delayed diagnosis. Early detection is a key step in reducing mortality rates, but conventional methods such as Pap smears and visual inspection with acetic acid (VIA) still face obstacles such as limited medical personnel, subjectivity of results, and low screening coverage in remote areas. Purpose: to analyze the potential application of artificial intelligence (AI) as an innovative solution to improve the effectiveness and efficiency of early detection of cervical cancer in Indonesia. Method: The study used a descriptive qualitative approach through a literature review of scientific journals, international agency reports (WHO, GLOBOCAN), and national policies related to digital health transformation. Results: The study shows that the application of deep learning-based AI can increase the sensitivity and specificity of detection to over 90%, speed up the analysis process from day to minute, and reduce the operational costs of examinations by up to 40%. In addition, AI has the potential to expand the scope of screening and strengthen the national health referral system through digital integration and cloud-based telemedicine. However, the main challenges faced include data privacy issues, algorithmic bias, legal liability, and digital infrastructure gaps that must be addressed with strong ethical policies and oversight. Conclusion: The application of AI in early detection of cervical cancer is a strategic step towards a more equitable, efficient, and sustainable healthcare system in Indonesia, provided that it is implemented responsibly, transparently, and with a focus on patient safety.