Bringing Cervical Cancer Screening Closer to Women: Feasibility of Artificial Intelligence and Remote Assessment in Primary Health Care

TL;DR

This study shows that AI and remote experts can effectively screen for cervical cancer in a single visit, making it easier for women to access care.

Contribution

Demonstrates the feasibility of AI and remote assessment for cervical cancer screening in primary healthcare.

Findings

AI achieved 86.7% sensitivity and 92.0% specificity in cervical cancer screening.

Remote experts had high sensitivity but low specificity and accuracy compared to AI.

The AI-driven Smart Scope® CX test is a viable single-visit screen-and-triage tool.

Abstract

The objective was to assess the feasibility of image-based methods for screening and triaging women in a single visit by: (i) a trained but inexperienced nurse, (ii) remote expert review via a web system, (iii) an artificial intelligence (AI) model.

Sexually active, non-pregnant women (25–65 years) were screened using visual inspection method Cervical images captured with Smart Scope® CX were assessed independently by nurses, remote experts, and AI, with assessors blinded to each other. Referrals for colposcopy were based on remote expert evaluations followed by colposcopy/biopsy.

Among 871 women screened, AI identified 205 positives; experts identified 201. Colposcopy was performed on 69 women, 40 of them had a biopsy. Compared to histopathology, AI achieved 86.7% sensitivity, 92.0% specificity, and 90.0% accuracy (AUC = 0.894). Remote experts showed high sensitivity (86.7%) but low specificity (32%) and accuracy (52.5%).

This study provides proof of concept for the feasibility of the AI-driven Smart Scope® CX test as a single-visit “screen-and-triage” tool in primary healthcare settings. Additionally, remote expert assessment demonstrating performance comparable to colposcopy indicates its potential as an alternative triage method in low-resource settings.

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