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A Prospective Study to Assess the Utility of Artificial Intelligence-driven Cervical Screening Using Smart Scope

Sukanya Dhar¹, Mriganka Mouli Saha¹, Sourav Sarkar¹

¹Department of Obstetrics and Gynaecology, College of Medicine and JNM Hospital, WBUHS, Kalyani, West Bengal, India.

Journal of Mid-Life Health

|May 13, 2026

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Artificial intelligence (AI) shows promise in cervical cancer screening, demonstrating high specificity and negative predictive value. While AI is a valuable adjunct tool, further refinement is needed for standalone use in detecting precancerous lesions.

Area of Science:

Oncology
Medical Imaging
Artificial Intelligence

Background:

Cervical cancer is a leading cause of cancer death in women globally, primarily caused by high-risk human papillomavirus.
Early detection and treatment of precancerous lesions, possible within a 10-year window, can prevent approximately 90% of cases.
The World Health Organization aims for cervical cancer elimination by 2030 through increased screening and treatment coverage.

Purpose of the Study:

To compare the efficacy of conventional Pap smear cytology with artificial intelligence (AI)-based analysis using Smart Scope for cervical cancer screening.
To evaluate the diagnostic performance of AI in identifying cervical precancerous lesions and malignancies.

Main Methods:

A prospective, cross-sectional study involving 128 women at a tertiary care center.

Keywords:

Artificial intelligence Smart Scope cervical cancer conventional cytology low-resource settings

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Cervical screening was performed using Smart Scope imaging followed by AI-based analysis.

Findings were statistically compared against conventional screening methods.

Main Results:

AI-assisted screening achieved high specificity (96.0%) and negative predictive value (99.2%) for cervical cancer detection.
AI correctly identified 89.8% of cases as negative for intraepithelial lesion or malignancy.
AI facilitated rapid image analysis, reduced diagnostic variability among gynecologists, and minimized interpretation subjectivity.

Conclusions:

AI-based image analysis shows potential as a supplementary tool in cervical cancer screening.
Current AI technology lacks the reliability for standalone cervical cancer screening.
Further research and clinical integration are necessary to enhance AI's effectiveness in cervical cancer screening.