Evaluating the Feasibility of Machine-Learning-Based Predictive Models for Precancerous Cervical Lesions in Patients Referred for Colposcopy.

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.

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.

Who cites it

3 citing papers in PubMed, 12 citations in OpenAlex.

1. A pilot study of upcycled smartphone-based colposcopy for visual inspection of cervix performed by community healthcare workers in rural Vietnam.International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics · 2025
   Article
2. Development and validation of artificial intelligence-based analysis software to support screening system of cervical intraepithelial neoplasia.Scientific reports · 2024
   Article
3. A preliminary attempt to use radiomic features in the diagnosis of extra-articular long head biceps tendinitis.Magma (New York, N.Y.) · 2023
   Article

Corrections and comments

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

Authors and funding

6 authors at 2 institutions in 1 country.

Funding

Abstract

PubMed holds no abstract for this paper.

Indexed as