Early Cervical Cancer Detection and the Importance of AI-Based Health Diagnostics
Cervical cancer is classified as one of the most preventable cancers among women worldwide. Yet, early diagnosis remains challenging in many countries, often leading to severe outcomes. In low- and middle-income countries, limited access to trained pathologists and insufficient screening infrastructure results in low screening rates and delayed detection. To address this, the World Health Organization (WHO) has announced a global strategy to eliminate cervical cancer by 2030, highlighting AI-based health diagnostics as a practical solution.
AI technology leverages high-precision image analysis and lesion detection to reduce the burden on healthcare professionals while maintaining consistent diagnostic quality. Traditional cervical cancer screening often relies on visual inspection with acetic acid (VIA) or Pap smear cytology, which are subject to human interpretation and can lead to errors. AI can analyze large volumes of samples quickly, providing quantitative, visualized results that assist clinical decision-making.
Currently, two leading domestic companies specializing in cervical cancer AI solutions are AIDOT and Noul. While both focus on medical AI, they differ in screening method (VIA vs. cytology), device structure, operational environment, and market strategy. AIDOT’s recently introduced portable colposcope-based on-device AI technology is recognized not only for technical sophistication but also for expanding healthcare accessibility.
AIDOT: Portable Colposcope-Based VIA AI Diagnosis with On-Device Technology
AIDOT offers Cerviray AI, which analyzes high-resolution cervical images captured via VIA and provides real-time visualization of lesion presence, suspicious areas, and probability scores. Notably, the entire process runs on AIDOT’s proprietary portable colposcope, combining a high-resolution camera, LED illumination, AI chipset, and touchscreen display.
The on-device AI eliminates the need for external pathology slides or network connectivity, delivering results in approximately five seconds. This independence from cloud infrastructure is particularly advantageous in resource-limited settings.
Unlike fixed hospital equipment, AIDOT’s solution can be rapidly deployed in community health centers, rural clinics, and mobile screening units. This aligns with WHO’s recommendation to screen at least 70% of women over 35 to achieve cervical cancer elimination goals. The device’s AI is optimized to maintain high accuracy even on lightweight hardware, and pilot deployments in the Philippines, Indonesia, and Mongolia have demonstrated operational feasibility. AIDOT envisions expanding this platform to other cancers, such as breast and skin cancer.
Noul: Cytology-Based Automation for Standardized Medical Diagnosis
Noul’s miLab CER automates cytology-based cervical cancer screening. The device scans slides, analyzes cellular abnormalities via an integrated AI engine, and generates a PDF report—all automatically on-site.
By adhering to traditional pathology workflows while integrating automation, Noul’s solution reduces diagnostic time, minimizes errors, and standardizes readings. The AI identifies suspicious cells, provides reliability scores, marks lesion locations, and tracks multi-reader history, supporting final clinical decisions.
Noul’s technology is already deployed in major Korean hospitals and is listed in WHO and UNITAID technical guidelines. It is particularly suited for public health institutions in Africa, South America, and Southeast Asia, offering reliable diagnostics despite limited infrastructure. While the device’s initial installation cost is relatively high, its repeat-use and consistent performance provide long-term cost efficiency.
Screening Approach and Strategic Positioning
AIDOT uses visual inspection-based AI, offering rapid readings and flexible deployment, whereas Noul focuses on high-precision cytology, ideal for hospital environments requiring detailed pathology.
From a business perspective, AIDOT operates as a platform: its colposcope enables AI analysis, patient data management, cloud integration, and API expansion, allowing fast scalability for community, municipal, and national health programs. This approach is well-suited for recurring screenings and national health initiatives.
Noul maintains a device-centric sales model, targeting public procurement channels. Its all-in-one cytology scanner can be installed in hospitals and used consistently without additional training, making it attractive for large-scale international projects endorsed by WHO.
For investors, AIDOT emphasizes scalability and rapid market penetration, while Noul highlights stability and technical reliability. Both companies, however, play critical roles in advancing AI-driven cervical cancer prevention.
Medical Learner Blog / July 23, 2025
