Bibliometric analysis of the application of artificial intelligence techniques in bacteriology: a PRISMA-guided research agenda.

ABSTRACT:

Introduction

The integration of artificial intelligence (AI) into bacteriology has marked a pivotal advancement by enabling the analysis of large-scale microbiological datasets. Despite growing adoption, significant research gaps persist, hindering the full exploitation of AI's potential in bacterial research and diagnostics.

Objective

To analyze global scientific production on the application of AI techniques in bacteriology and propose a future research agenda based on bibliometric trends.

Methods

This study conducts a bibliometric analysis of artificial intelligence (AI) applications in bacteriology, explicitly guided by the PRISMA 2020 framework. Unlike traditional reviews, this approach combines PRISMA's methodological rigor with bibliometric techniques to map sc

SUBMITTER: Velasco Cardona DC 

PROVIDER: S-EPMC12481518 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature