Application of artificial intelligence in cervical cytology: a systematic review of deep learning models, datasets, and reported metrics.

ABSTRACT:

Introduction

The use of artificial intelligence (AI) in cervical cytology has increased substantially due to the need for automated tools that support the early detection of precancerous lesions.

Methods

This systematic review examined deep learning models applied to cervical cytology images, focusing on the architectures used, the datasets employed, and the performance metrics reported. Articles published between 2022 and 2025 were retrieved from Scopus using PRISMA methodology. After applying inclusion criteria and full-text screening, 77 studies were included for RQ1 (models), 75 for RQ2 (datasets), and 71 for RQ3 (metrics).

Results

Hybrid models were the most prevalent (56%), followed by convolutional neural networks (CNNs) and a growing number of Vision Transform

SUBMITTER: Valles-Coral MA 

PROVIDER: S-EPMC12807953 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature