Evidence map›Paper›PMID 41867352›Full record

ArticleInternational journal of public health2026

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

Saritha Shamsunder, Leela Digumarti, Bhagyalaxmi Nayak, Vasantha Dasari, Archana Mishra, Anita Kumar, Sony Nanda, Jugal Kishore, Nishi Choudhary

Abstract read
In one paragraph

Article in International journal of public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Saritha ShamsunderDepartment of Obstetrics and Gynecology, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, India.
Leela DigumartiDepartment of Obstetrics and Gynecology, KIMS-ICON Hospital, Visakhapatnam, India.
Bhagyalaxmi NayakDepartment of Gynecological Oncology, Acharya Harihar Post Graduate Institute of Cancer, Cuttack, Odisha, India.
Vasantha DasariDepartment of Obstetrics and Gynecology, KIMS-ICON Hospital, Visakhapatnam, India.
Archana MishraDepartment of Obstetrics and Gynecology, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, India.
Anita KumarDepartment of Obstetrics and Gynecology, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, India.
Sony NandaDepartment of Gynecological Oncology, Acharya Harihar Post Graduate Institute of Cancer, Cuttack, Odisha, India.
Jugal KishoreDepartment Community Med, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, India.
Nishi ChoudharyDepartment of Obstetrics and Gynecology, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: 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. Methods: 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. Results: 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%). Conclusion: 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.

Indexed as

Artificial IntelligenceEarly Detection of CancerPrimary Health CareUterine Cervical NeoplasmsAdultAgedColposcopyFeasibility StudiesFemaleHumansIntelligent SystemsMiddle AgedSensitivity and SpecificityTriageartificial intelligencecervical cancer screeningdigital screening devicelow-resource settingsscreen-triage-treatVIA-VILI

Identifiers

PMID41867352
PMCPMC12999539

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.